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Paper Citation Record · LEDGER

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection

As of 19 August 2026, this Paper Citation Record lists 90 of 90 outbound references and 0 inbound Pith citation observations for arXiv:2608.09147.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2608.09147 v1

Coverage vector

measured 90 of 90 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T22:42:54.362361Z

measured 90 of 90 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

90 of 90 outbound references displayed

  • verified exact1
  • verified fuzzy52
  • unresolved36
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 78187b37-94e9-4dd8-b4af-ff1488dd0a7c · outbound

This paper cites Qwen3-VL Technical Report.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Qwen3-VL Technical Report

Reference 1

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source=pdf_text observed=2026-08-11T22:42:52.373661Z digest=sha256:9c6e77ec5f2fd5b7b8645aefe0d2338ae5b65fa2e3b365a5b7d1ebd451e05dc2

Observation a7ac1406-829b-40fc-b1e9-169ad44954c1 · outbound

This paper cites Qwen2.5-VL Technical Report.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Qwen2.5-VL Technical Report

Reference 2

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source=pdf_text observed=2026-08-11T22:42:52.454808Z digest=sha256:9fdf83887bd7e64912c2c52e6831a205e2669701905c72546d75caa5504c225c

Observation c3ad01e8-def6-4e6c-8e24-bc721f91da91 · outbound

This paper cites Omni3d: A large benchmark and model for 3D object detection in the wild.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Omni3d: A large benchmark and model for 3D object detection in the wild

Reference 3

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source=pdf_text observed=2026-08-11T22:42:52.504746Z digest=sha256:5bd2689003b1caa8ce053c441793e9428ef247b097e9dc8972a1ef83626c0282

Observation 90a70e41-f54d-47b9-98c3-3f3cd25b3930 · outbound

This paper cites M3D-RPN: Monocular 3D region proposal network for object detection.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection M3D-RPN: Monocular 3D region proposal network for object detection

Reference 4

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source=pdf_text observed=2026-08-11T22:42:52.554749Z digest=sha256:cd1b583182b2fcda0c0f5428a50b2cc5d46158cd9d1052e29f040aafe36e5c02

Observation 3ce193aa-cddf-4f74-8175-91e0ac7532a8 · outbound

This paper cites Kinematic 3d object detection in monocular video.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Kinematic 3d object detection in monocular video

Reference 5

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source=pdf_text observed=2026-08-11T22:42:52.604817Z digest=sha256:44bf31b9f11d9fe597ef703b2d3bf39a43ea831909fb177184da2b060bae5191

Observation 3f1303ee-8007-4af9-bfb5-4c4363cff98c · outbound

This paper cites nuscenes: A multimodal dataset for autonomous driving.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection nuscenes: A multimodal dataset for autonomous driving

Reference 6

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source=pdf_text observed=2026-08-11T22:42:52.654732Z digest=sha256:349af5d0f0595a1da43d88463571c463acf360f59747736a4964422f41bd803e

Observation 24e6dcf1-8213-4c00-8286-fc3476ad42fc · outbound

This paper cites Vip-llava: Making large multimodal models understand arbitrary visual prompts.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Vip-llava: Making large multimodal models understand arbitrary visual prompts

Reference 7

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source=pdf_text observed=2026-08-11T22:42:52.724730Z digest=sha256:9621cf004e7940e25375e873d5ad6a44e9519fcfec02282e4739a71b90690962

Observation 5e130e7f-2d26-456c-baa8-617872a5d2ca · outbound

This paper cites End-to-end object detection with transformers.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection End-to-end object detection with transformers

Reference 8

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source=pdf_text observed=2026-08-11T22:42:52.793808Z digest=sha256:39f1440b0ce1e8d9ecaa901ff86ca5f43b54a3ab7b0d770987f0a6ecba038ab1

Observation 83832680-966a-4a5f-8c4e-db20adbe28da · outbound

This paper cites Spatialvlm: Endowing vision-language models with spatial reasoning capabilities.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Spatialvlm: Endowing vision-language models with spatial reasoning capabilities

Reference 9

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source=pdf_text observed=2026-08-11T22:42:52.824736Z digest=sha256:c5099868a56c6f2d2a94578ea6a3189d1b36811e87ab72018598c1f0a9190341

Observation e6c6e7a1-3ae5-4715-be06-b98e34dc481e · outbound

This paper cites End-to-end autonomous driving: Challenges and frontiers.TPAMI, 2024.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection End-to-end autonomous driving: Challenges and frontiers.TPAMI, 2024

Reference 10

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source=pdf_text observed=2026-08-11T22:42:52.874733Z digest=sha256:e700b8be2a05cca7c7e3009879745f63a0a080349c8cf769928994a4eff8bfbb

Observation 8330c96b-fc03-4c7e-9145-d3301ba91440 · outbound

This paper cites Group detr: Fast detr training with group-wise one-to-many assignment.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Group detr: Fast detr training with group-wise one-to-many assignment

Reference 11

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source=pdf_text observed=2026-08-11T22:42:52.944744Z digest=sha256:03614f2d484b7e8e8a25863298aa0362cb929859d0500b938c4144857a301d22

Observation e2417d19-70ef-4c87-bf52-e655c967885d · outbound

This paper cites Monocular 3D object detection for autonomous driving.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Monocular 3D object detection for autonomous driving

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:52.981681Z digest=sha256:6562ecb0f76becce6628baec9bb257b09b2eb0c134f572a1e6e44075c1c68332

Observation dd181c65-09b5-4bea-b858-2538d2300357 · outbound

This paper cites Spatialrgpt: Grounded spatial reasoning in vision-language models.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Spatialrgpt: Grounded spatial reasoning in vision-language models

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:52.986671Z digest=sha256:73292a31dea52407bc33bd99652a32f50cd3a5f5e6af79b57a176535fd6be883

Observation 0c82e4ce-98f5-4ea0-a26e-f96ecbe88d26 · outbound

This paper cites VLM-3R: Vision-Language Models Augmented with Instruction-Aligned 3D Reconstruction.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection VLM-3R: Vision-Language Models Augmented with Instruction-Aligned 3D Reconstruction

Reference 14

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source=pdf_text observed=2026-08-11T22:42:53.000772Z digest=sha256:c25c840b0585b7da0361792427dd26aff584d3fdfd5cd1e98926bf20c5d8c8fd

Observation a4f199b9-b3b4-4dc8-a599-45da86db1309 · outbound

This paper cites Are we ready for autonomous driving? the kitti vision benchmark suite.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Are we ready for autonomous driving? the kitti vision benchmark suite

Reference 15

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verified fuzzy
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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:53.005052Z digest=sha256:6f38218d75a47454a45c7a522774e77722cbe6f75fbf0801466b74ccb48c112e

Observation 2841caaf-7f15-4478-9468-6ef4ea17803c · outbound

This paper cites Omni-rgpt: Unifying image and video region-level understanding via token marks.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Omni-rgpt: Unifying image and video region-level understanding via token marks

Reference 16

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:53.010574Z digest=sha256:b5ccd019f5e8d97e3e97c8203c155a16835bfe38e82879f6041c8344cd98ab79

Observation 522112df-aa3b-401d-8aee-8c89481b5409 · outbound

This paper cites 3d-llm: Injecting the 3d world into large language models.NeurIPS, 2023.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection 3d-llm: Injecting the 3d world into large language models.NeurIPS, 2023

Reference 17

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:53.073375Z digest=sha256:9efd3c4e6fd0d5b55ed18fafed6261ad4c4d164db1476545657da838cad22fe9

Observation 3881e149-4a7e-4de0-a851-8ce5edee5fcc · outbound

This paper cites G 2vlm: Geometry grounded vision language model with unified 3d reconstruction and spatial reasoning.arXiv preprint arXiv:2511.21688, 2025.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection G 2vlm: Geometry grounded vision language model with unified 3d reconstruction and spatial reasoning.arXiv preprint arXiv:2511.21688, 2025

Reference 18

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source=pdf_text observed=2026-08-11T22:42:53.174829Z digest=sha256:0793c4b57462f0febf85d79d1b73d9f1c2862ea82c9fa14ff742fd382f438b57

Observation 18419ca6-7380-4cf1-aff1-ad51f31b019a · outbound

This paper cites Monodtr: Monocular 3D object detection with depth-aware transformer.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Monodtr: Monocular 3D object detection with depth-aware transformer

Reference 19

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:53.262321Z digest=sha256:27de80baa93ea1e77908faf60844b30088819718def42d83ca8ea83f7a534db0

Observation 08e3fa61-7058-4d04-8939-88d2ac4f9c22 · outbound

This paper cites 3D-R1: Enhancing Reasoning in 3D VLMs for Unified Scene Understanding.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection 3D-R1: Enhancing Reasoning in 3D VLMs for Unified Scene Understanding

Reference 20

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source=pdf_text observed=2026-08-11T22:42:53.308959Z digest=sha256:fb6cd4eb6dd99af0a1eab13eae9d6cc7580aa764768033adc2f1d62ab393af4f

Observation 9b3aeba7-04ee-4f29-902a-354be8ffe679 · outbound

This paper cites Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models

Reference 21

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source=pdf_text observed=2026-08-11T22:42:53.321616Z digest=sha256:77982d75336551c7673ff6fa55ffa75451f07205ff566950751f4b9b25bd6bf9

Observation e7904973-73c8-45a1-89f2-b77e58085ba8 · outbound

This paper cites MonoMAE: Enhancing monocular 3D detection through depth-aware masked autoencoders.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection MonoMAE: Enhancing monocular 3D detection through depth-aware masked autoencoders

Reference 22

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:53.327359Z digest=sha256:d5347f86cea7323113adf087cf16378e72466835bd832bf777d5d0623e99e881

Observation 6a05925d-86a8-43d2-a165-6ff18efb440a · outbound

This paper cites OpenVLA: An Open-Source Vision-Language-Action Model.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection OpenVLA: An Open-Source Vision-Language-Action Model

Reference 23

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source=pdf_text observed=2026-08-11T22:42:53.333231Z digest=sha256:010ed267ceb387dd404274e5bb536d22bab51166ba7c3698fc706d1cba90d218

Observation 854d2589-ba1f-4f56-8e6f-747c5a5ef5cb · outbound

This paper cites Deviant: Depth equivariant network for monocular 3D object detection.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Deviant: Depth equivariant network for monocular 3D object detection

Reference 24

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verified fuzzy
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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:53.342029Z digest=sha256:8d278b8b02c1dc92d60cefd3e917b6c4a10d09756c497f1deccb0482fa61e12a

Observation 2fb6ed6b-45af-4bfa-8ef9-154926dcb3a3 · outbound

This paper cites GrooMeD-NMS: Grouped mathematically differen- tiable nms for monocular 3D object detection.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection GrooMeD-NMS: Grouped mathematically differen- tiable nms for monocular 3D object detection

Reference 25

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:53.346486Z digest=sha256:c51aacabacb4f04a9abf7aef1bbead2c8a2d10c7b9ce389f45f02d6f01ff922d

Observation e6c1ab68-4aab-4800-bec9-de66a139910f · outbound

This paper cites Lisa: Reasoning segmentation via large language model.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Lisa: Reasoning segmentation via large language model

Reference 26

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source=pdf_text observed=2026-08-11T22:42:53.356112Z digest=sha256:deebb36bc578d903db7c526b09a3735e82e0322d608170f36a8ba8f391ac060c

Observation 18000c34-1f1c-4aa3-bfdd-8bcec243e38f · outbound

This paper cites Spatial forcing: Implicit spatial representation alignment for vision-language-action model.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Spatial forcing: Implicit spatial representation alignment for vision-language-action model

Reference 27

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source=pdf_text observed=2026-08-11T22:42:53.377319Z digest=sha256:a14a9323aeada8a9791d059c6ee520c57444808acea211487c37ec5909b852c8

Observation cba93358-baad-4f5c-83e3-dfc086a59282 · outbound

This paper cites Diversity matters: Fully exploiting depth clues for reliable monocular 3D object detection.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Diversity matters: Fully exploiting depth clues for reliable monocular 3D object detection

Reference 28

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verified fuzzy
raw_fallback, observed 2026-08-11T22:42:57.330239Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:53.384759Z digest=sha256:8b861644671ec1cf36091a5b405a0aac4ee956a0ed91adf9965ca36aed7919fe

Observation 119f86c7-41cd-4bff-8152-1b4cccf1686d · outbound

This paper cites Unimode: Unified monocular 3d object detection.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Unimode: Unified monocular 3d object detection

Reference 29

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:53.408946Z digest=sha256:7d22a5c008b97b87199cf090f02529e9f0707cb68ba7056c702ef3dca4f5ff13

Observation 8fa1b647-66f7-4b60-a412-b5f0b4ff52c9 · outbound

This paper cites Draw-and-Understand: Leveraging Visual Prompts to Enable MLLMs to Comprehend What You Want.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Draw-and-Understand: Leveraging Visual Prompts to Enable MLLMs to Comprehend What You Want

Reference 30

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:42:53.434907Z digest=sha256:bf7fcde98a34257b5460359170c943d4f4ebc6c59751d773d9d57e44ef77378d

Observation 9f483add-fae9-40b5-a7c2-0fd6e8f13984 · outbound

This paper cites Monotakd: Teaching assistant knowledge distillation for monocular 3d object detection.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Monotakd: Teaching assistant knowledge distillation for monocular 3d object detection

Reference 31

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raw_fallback, observed 2026-08-11T22:42:57.240456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:53.458216Z digest=sha256:b427177ac3bd1852112d4c61ed8b690a6c8b4ca33169c64e855b70011282c353

Observation eabbbc06-55f9-49f3-8c57-32305fff15f0 · outbound

This paper cites Edge assisted real-time object detection for mobile augmented reality.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Edge assisted real-time object detection for mobile augmented reality

Reference 32

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verified fuzzy
raw_fallback, observed 2026-08-11T22:42:57.200955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:53.467345Z digest=sha256:667f5bdbce5df2476bd5771e1f441c2c778b4e43bc3df05eaa764cb102336857

Observation b0bc0143-b102-4693-8248-9b421bbfada8 · outbound

This paper cites Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection

Reference 33

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:42:53.483168Z digest=sha256:0ecb6102d7f4a171e661c50086f3056e30e6bff868d5ffc1210559c5c0cfdfd3

Observation 2a606330-b530-4f66-8ae2-80de9a39a6b7 · outbound

This paper cites Monocular 3D object detection with bounding box denoising in 3D by perceiver.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Monocular 3D object detection with bounding box denoising in 3D by perceiver

Reference 34

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raw_fallback, observed 2026-08-11T22:42:57.151658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:53.495442Z digest=sha256:3b9da068d0797a36fb6d4e48c1c51446212624a39b9d132b751fad33cb33460f

Observation 7da3dcbf-0e6a-4bdc-9567-7f86343cfc96 · outbound

This paper cites SMOKE: Single-stage monocular 3D object detection via keypoint estimation.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection SMOKE: Single-stage monocular 3D object detection via keypoint estimation

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:57.090921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:53.509612Z digest=sha256:bacf2c093043337a9d540ed3cd5c9ef6d90c8f6e45ebcbc40c1e12c549321ac7

Observation 879ac075-af12-42e5-bac9-025c6a08f40f · outbound

This paper cites Geometry uncertainty projection network for monocular 3D object detection.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Geometry uncertainty projection network for monocular 3D object detection

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:57.045583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:53.545831Z digest=sha256:50d83a9c558834ba18e078b01ca5a8db9b6588865e0fb84b9b778a5f601be9f0

Observation aec03b03-f803-4a25-b210-5627b9eb3029 · outbound

This paper cites Delving into localization errors for monocular 3D object detection.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Delving into localization errors for monocular 3D object detection

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:57.008203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:53.561955Z digest=sha256:ea94dbf55ea6a689d34a1326518afecc8acfb1fa2df7c70494301668bb036b9e

Observation ee06c864-b72f-4a19-9421-5aadf4f8dd37 · outbound

This paper cites Spatiallm: Training large language models for structured indoor modeling.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Spatiallm: Training large language models for structured indoor modeling

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:56.972882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:53.577772Z digest=sha256:8ac2d1835688b7bacdd586773a410cfb8fffb9ae47d48f7b1ae742454e441b7a

Observation de0e65f4-6035-4210-bfc4-513c3c0464cf · outbound

This paper cites 3D bounding box estimation using deep learning and geometry.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection 3D bounding box estimation using deep learning and geometry

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:56.930618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:53.606345Z digest=sha256:46081ba44aadfe0695f8b8b6358254732783a26d7c400edf8b76f42dd9513452

Observation d2edd1d2-f4b0-4ee1-a4aa-9b64798b99b1 · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection DINOv2: Learning Robust Visual Features without Supervision

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-11T22:42:53.654995Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:42:53.654995Z digest=sha256:49febf408a7c5e1876c173f85dacc6a7325e845488bbf9a903cc11fd0ef74069

Observation 4efcfa78-7ee7-4a20-a2dc-9449d139d4b3 · outbound

This paper cites Learning occupancy for monocular 3D object detection.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Learning occupancy for monocular 3D object detection

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:56.883468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:53.681356Z digest=sha256:3b606a00c3e0280ce1619553173a69788a89e54717c97b1b31569ea94e3d3d74

Observation e5878834-c7d7-4dae-b050-5a6e29c0a0e9 · outbound

This paper cites UniDepthV2: Universal monocular metric depth estimation made simpler, 2025.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection UniDepthV2: Universal monocular metric depth estimation made simpler, 2025

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:56.861742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:53.704564Z digest=sha256:0aa593c43ef1ac87f52904d7a49a6140321f1dbaddaa3b7c3caf2063b5066bbb

Observation 953e5b24-f537-4c0e-aaec-96d8beb345df · outbound

This paper cites MonoDGP: Monocular 3D Object Detection with Decoupled-Query and Geometry-Error Priors.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection MonoDGP: Monocular 3D Object Detection with Decoupled-Query and Geometry-Error Priors

Reference 43

Resolution
verified exact
local_arxiv, observed 2026-08-11T22:42:54.776140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:53.714226Z digest=sha256:92a3fc6e2f25723a0a2ddc07b83027af5f68cc969b08552596b1d636ae7d10fd

Observation 1ea534cc-fa1d-4cfd-94df-c0252b11ad62 · outbound

This paper cites Monoground: Detecting monocular 3D objects from the ground.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Monoground: Detecting monocular 3D objects from the ground

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:56.804138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:53.727980Z digest=sha256:6ae1ea80c3f6f7ffa609942ea9ef9bc606908ee42a4052f5ea3eedd47a4983fc

Observation 16df908f-e0ad-450b-939a-d13e814696af · outbound

This paper cites Loc3r-vlm: Language- based localization and 3d reasoning with vision-language models, 2026.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Loc3r-vlm: Language- based localization and 3d reasoning with vision-language models, 2026

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:56.756753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:53.745953Z digest=sha256:36f7dd220ad9f2e0afe2be51e106cc1b2c0db9e5a962dc4f84a1f39dc51f55c7

Observation bca78183-3112-4a8d-96c9-4d8e2608b023 · outbound

This paper cites VLM-R1: A Stable and Generalizable R1-style Large Vision-Language Model.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection VLM-R1: A Stable and Generalizable R1-style Large Vision-Language Model

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-11T22:42:53.802940Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:42:53.802940Z digest=sha256:7c8f3151a433f1e478e6e5d7b87ead99bd286d8a52b6d751a7a52ee538bc6a71

Observation 7b3fb06e-6f17-4803-91ac-a99841a826c4 · outbound

This paper cites PointRCNN: 3D object proposal generation and detection from point cloud.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection PointRCNN: 3D object proposal generation and detection from point cloud

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:56.712804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:53.841145Z digest=sha256:b4ec3b5a044882c29da991a8f548b0ebe0ca517bb67b89cb78f74b7457215e79

Observation 3cd6c1ee-10c7-48bc-846a-b76ec98288cb · outbound

This paper cites Geometry- based distance decomposition for monocular 3D object detection.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Geometry- based distance decomposition for monocular 3D object detection

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:56.689327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:53.871820Z digest=sha256:4a18fdcab1086e1b1bbce331e08d8614f5c9db649cc023d58f3463da0a497ac7

Observation 2d0e8530-136e-49d9-bc0b-c832c3f409d0 · outbound

This paper cites Geometry- based distance decomposition for monocular 3D object detection.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Geometry- based distance decomposition for monocular 3D object detection

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:56.664185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:53.909511Z digest=sha256:94e9c766257a2f6008df034bd7fe49e7471fc6cbf2d722c460c7dfe06107878d

Observation 3736ae73-b70a-4964-976f-10b93280fe06 · outbound

This paper cites What does clip know about a red circle? visual prompt engineering for vlms.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection What does clip know about a red circle? visual prompt engineering for vlms

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:56.625339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:53.919487Z digest=sha256:aca0bd40fff7257cfdaafc63023eafa0dc50a580191d2e4d4136590927428dc7

Observation 5d14ff63-74d3-463f-8b45-db1aa07dab8e · outbound

This paper cites EVA-CLIP: Improved Training Techniques for CLIP at Scale.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection EVA-CLIP: Improved Training Techniques for CLIP at Scale

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-11T22:42:53.929902Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:42:53.929902Z digest=sha256:169d290057f31f97bcc18f0c525cc247369653f97dbcac04def92fcf6b605d85

Observation a94ea378-f03e-426e-a421-ac98d58523bf · outbound

This paper cites Cambrian-1: A fully open, vision-centric exploration of multimodal llms, 2024.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Cambrian-1: A fully open, vision-centric exploration of multimodal llms, 2024

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:56.533136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:53.936623Z digest=sha256:7c057ae17ef4f22e81a7c4182366103314683b899e675d311c50870ca3b3826c

Observation fdf1289f-5f3e-4688-a90a-bdd4fcf1a7a2 · outbound

This paper cites Vggt: Visual geometry grounded transformer.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Vggt: Visual geometry grounded transformer

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:56.510886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:53.942526Z digest=sha256:fa1c1e4fe1557644f43dd2bb76dba6abcb903ed9e1a3f22b84ae09157478c10c

Observation 9ca04145-97e4-400f-a4e4-0db12d266f7e · outbound

This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-11T22:42:53.951768Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:42:53.951768Z digest=sha256:280fb597eb4761ed3c0e176a402714c8ed07df4b8fdc2579928ff77e5cd81332

Observation 464d571d-5e91-490f-9035-36f154fe330c · outbound

This paper cites Moge-2: Accurate monocular geometry with metric scale and sharp details.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Moge-2: Accurate monocular geometry with metric scale and sharp details

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:56.424408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:53.974741Z digest=sha256:5caf0c835bcd1591c11e7fcaabb120059b12b8de5283ec31be8af2b06b9fd116

Observation 264621be-d8a0-4199-98c3-3d909f425a0a · outbound

This paper cites Embodiedscan: A holistic multi-modal 3d perception suite towards embodied ai.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Embodiedscan: A holistic multi-modal 3d perception suite towards embodied ai

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:56.341262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:54.004744Z digest=sha256:e12667a8271a544b5acb7a48ab16f080dbebf0e094b93a39380bb84562bb62ec

Observation cdecedf8-bf46-43f3-92fe-1aefe629245a · outbound

This paper cites Probabilistic and geometric depth: Detecting objects in perspective.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Probabilistic and geometric depth: Detecting objects in perspective

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:56.294761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:54.064754Z digest=sha256:9648e000c545c18327b27863722595ab37e987ab2b6286d6303b9f97f83725b6

Observation e19fcf69-9e6f-48f5-851e-8e80b33591d3 · outbound

This paper cites N3d-vlm: Native 3d grounding enables accurate spatial reasoning in vision-language models.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection N3d-vlm: Native 3d grounding enables accurate spatial reasoning in vision-language models

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-11T22:42:54.081262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:42:54.081262Z digest=sha256:f1f8227c4dd5718c960e3f34335a768335e028989e57ee9f3498338bf4405a21

Observation 46524032-23a2-4784-bae8-7f75f1d48cda · outbound

This paper cites Ov-uni3detr: Towards unified open-vocabulary 3d object detection via cycle-modality propagation.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Ov-uni3detr: Towards unified open-vocabulary 3d object detection via cycle-modality propagation

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:56.224751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:54.091079Z digest=sha256:e8be93e3f3fae41e755e4853a55d941cce4da5fa08c1dc78e81fe07de1062dae

Observation 280fb01e-b9ca-4d1e-8300-ce9f1f413955 · outbound

This paper cites Monopgc: Monocular 3D object detection with pixel geometry contexts.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Monopgc: Monocular 3D object detection with pixel geometry contexts

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:56.164805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:54.103917Z digest=sha256:a2b44d022a8db3c233835c67eaee0eb0842039e2e352900ef6a977a248577256

Observation 5480dcd5-e064-4aa8-9866-feecab4c74cf · outbound

This paper cites FD3D: Exploiting foreground depth map for feature-supervised monocular 3D object detection.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection FD3D: Exploiting foreground depth map for feature-supervised monocular 3D object detection

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:56.128861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:54.109578Z digest=sha256:21b9c85cd011d3164be3f63e3c1f1c6395f3c0adaa439e5713423d9235c92fe8

Observation 8f9e0e7d-8bea-491f-939f-0d4de752dd4a · outbound

This paper cites Pointllm: Empower- ing large language models to understand point clouds.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Pointllm: Empower- ing large language models to understand point clouds

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:56.036818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:54.114238Z digest=sha256:274fe495192c7770ea12e5caae829ca9766470cf3e60311cfd86cddfb9815a47

Observation c64dd527-500d-4641-88e4-5c8dc94b5f5f · outbound

This paper cites MonoCD: Monocular 3D object detection with complementary depths.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection MonoCD: Monocular 3D object detection with complementary depths

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:56.008213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:54.127214Z digest=sha256:597f2b63cce608acfea7eaac23c870f30b3d4e941990df8981c217350baf7117

Observation 86720c4b-872d-48b3-8306-8fab8ba7e1a6 · outbound

This paper cites Qwen3 Technical Report.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Qwen3 Technical Report

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-11T22:42:54.139970Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:42:54.139970Z digest=sha256:aa957513feadd2e1bfeb0ed8d9412de16fe44c742b7340a923c67867754d4533

Observation 666854ce-4354-4e33-9547-1adc3248a3a9 · outbound

This paper cites Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4V.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4V

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-11T22:42:54.156474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:42:54.156474Z digest=sha256:f227c73b144f051380dc51c69068916cb94d61ae24d4f362dd0674ac236f8b24

Observation a210ecc5-89bc-4640-b532-515336f80c78 · outbound

This paper cites LISA++: An Improved Baseline for Reasoning Segmentation with Large Language Model.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection LISA++: An Improved Baseline for Reasoning Segmentation with Large Language Model

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-11T22:42:54.163754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:42:54.163754Z digest=sha256:52cdd205bddb7fd14060f5e48c2d14e8a89d0d63804c93094011e27835e9c0a9

Observation b6e47b97-ee27-49f9-906d-13d45745190f · outbound

This paper cites 3d-mood: Lifting 2d to 3d for monocular open-set object detection.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection 3d-mood: Lifting 2d to 3d for monocular open-set object detection

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:55.945609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:54.177913Z digest=sha256:7cc93c85da44e1824d71faf0efe8b17f56ef1fc27f8142110835e1c87477726b

Observation caaacff0-c253-4a51-aff0-1cb35087c041 · outbound

This paper cites Open vocabulary monocular 3d object detection.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Open vocabulary monocular 3d object detection

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:55.884809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:54.186433Z digest=sha256:8031a9650e71c3a07558e576593530775e958697aeb4f893a4c655759277e623

Observation a4526452-68b2-42d3-989d-a256912ba07c · outbound

This paper cites Dwyer, and Zezhou Cheng.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Dwyer, and Zezhou Cheng

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:55.786661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:54.191594Z digest=sha256:a876b43b685de71bdaa03d3cd67e9f755c0c635798858575306d890d60e06c3d

Observation bae92556-470c-47af-b0b5-9125361f0e94 · outbound

This paper cites Center-based 3D object detection and tracking.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Center-based 3D object detection and tracking

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:55.767320Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:54.197268Z digest=sha256:e4a9f7a6d253d19bc45f0741cfcaaec7b33acddc2f94ea239820008942df6d0f

Observation f71b29e5-d9df-4b87-922b-94e788bf33e9 · outbound

This paper cites Videorefer suite: Advancing spatial-temporal object understanding with video llm.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Videorefer suite: Advancing spatial-temporal object understanding with video llm

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:55.745716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:54.217735Z digest=sha256:d2617ea6aa0b23128fbff9f58d6dc69d9c8c8232802515f3f1d8d8537ce3feff

Observation 265460b4-e427-4e2b-bb7b-22a006fc1663 · outbound

This paper cites Detect anything 3d in the wild.arXiv preprint arXiv:2504.07958, 2025.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Detect anything 3d in the wild.arXiv preprint arXiv:2504.07958, 2025

Reference 72

Resolution
unresolved
no resolver link, observed 2026-08-11T22:42:54.233876Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:42:54.233876Z digest=sha256:ed6623bb5f6cfe878ab98fbdcae253e6ce0d7a211b3e00e0559c6e64e89a0f50

Observation 68317237-466c-47b3-ba67-da854cbe601c · outbound

This paper cites Monodetr: Depth-guided transformer for monocular 3D object detection.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Monodetr: Depth-guided transformer for monocular 3D object detection

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:55.713522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:54.240517Z digest=sha256:c8e3ec168e1ab683ed676e30c91bcd3e7efba9ed1c740084a1e08819753222b1

Observation 067c0e06-798b-4c3b-aa8c-2bb5dde42f51 · outbound

This paper cites Objects are different: Flexible monocular 3D object detection.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Objects are different: Flexible monocular 3D object detection

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:55.687279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:54.246579Z digest=sha256:5b46d7ba84f680684c6d3b40f7308b8c408256bcc1858ae95032187320715d55

Observation 25ffde4e-e80a-4ab3-a81a-fdbdc20ed98a · outbound

This paper cites Unleashing the power of chain-of-prediction for monocular 3d object detection.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Unleashing the power of chain-of-prediction for monocular 3d object detection

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:55.656889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:54.252044Z digest=sha256:0f30beb0de1d024a365cdfac431200f04f7877313e33f6367ec0c87fa2818114

Observation 209120c8-ddd5-4d61-af5d-9a23c15c4629 · outbound

This paper cites Detrs beat yolos on real-time object detection.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Detrs beat yolos on real-time object detection

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:55.623346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:54.256824Z digest=sha256:f90af533521b3cd12c1bb72fff478a850a968da8195228393be39175de7da3fd

Observation 09ba0257-7335-4fdc-a8f0-51d918e6005e · outbound

This paper cites 3D-VLA: A 3D Vision-Language-Action Generative World Model.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection 3D-VLA: A 3D Vision-Language-Action Generative World Model

Reference 77

Resolution
unresolved
no resolver link, observed 2026-08-11T22:42:54.268139Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:42:54.268139Z digest=sha256:100ec6c338a39c9eb4b74ae9dc5d732bdc464ad54cd2bea93ee47316c0d2ffe6

Observation 48466a47-025c-463c-abaa-6a85fd4ab12c · outbound

This paper cites Monoatt: Online monocular 3D object detection with adaptive token transformer.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Monoatt: Online monocular 3D object detection with adaptive token transformer

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:55.593413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:54.273611Z digest=sha256:765256aa7a7df4395be31a3533a905055b3693ccffd79ad5d19d11670d8fe203

Observation 78c634d8-8a69-4f21-9457-e6c66febb797 · outbound

This paper cites Single image 3d object detection and pose estimation for grasping.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Single image 3d object detection and pose estimation for grasping

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:55.560087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:54.279104Z digest=sha256:a043e601a05bd4304f3ba62d9dd69fd82fc8e9717987d356b2162df2295e4234

Observation a4b1f79c-a60d-42a6-9eb1-19685acb8aa7 · outbound

This paper cites move closer to camera.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection move closer to camera

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:55.535717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:54.283530Z digest=sha256:993f53186cf44a0d25066216bccd3df4a990a47455757b0a1608b004f30b157d

Observation fe137f5a-5526-4908-8936-156107be54eb · outbound

This paper cites 16 Table 8: Oracle study under the Omni3D evaluation protocol.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection 16 Table 8: Oracle study under the Omni3D evaluation protocol

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:55.474764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:54.290234Z digest=sha256:0af54813b18e51b6132fae1a857c3efd83dba112eb0f939ce7d7b37a12b16ed4

Observation 9ce2ca16-51c1-4e81-beb9-a133e672eac4 · outbound

This paper cites an unresolved cited work.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Unresolved cited work

Reference 83

Resolution
unresolved
raw_fallback, observed 2026-08-11T22:42:55.424527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:54.298620Z digest=sha256:819ae37808871cbacb45dc466e34a70b77d7da096b3684af59a0f62bced6819f

Observation cecaa751-2c39-4b7a-8475-e19b7c5e7c95 · outbound

This paper cites an unresolved cited work.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Unresolved cited work

Reference 84

Resolution
unresolved
raw_fallback, observed 2026-08-11T22:42:55.402688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:54.306001Z digest=sha256:7588f9e673373c3d82c25131b3c4ce7f67d0c62e6a7fb74ea123cb0e036fe6f4

Observation f375d25c-8e8e-419b-9642-eeb43dda1b2e · outbound

This paper cites We use Tmax = 2 in all experiments.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection We use Tmax = 2 in all experiments

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:55.354741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:54.311679Z digest=sha256:14e6584f240194ba53e2c292fa07f4c24d3503354e2842cf243e0292c786fa7a

Observation 792b567a-df36-4b27-ba30-44d6946a4c14 · outbound

This paper cites Indoor Scenes.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Indoor Scenes

Reference 86

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:42:55.329673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:54.317038Z digest=sha256:6db4a0caa305a4ca6fad1aee29ec65213da913e84009efdb8bd737b003a49b2f

Observation bd82f07e-8e42-4f5f-9ca6-0f0d5ec7da7a · outbound

This paper cites an unresolved cited work.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Unresolved cited work

Reference 87

Resolution
unresolved
raw_fallback, observed 2026-08-11T22:42:55.311937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:54.325974Z digest=sha256:c984016e01667911bdf950b08c47b34daf63e1b41212de2d9c99866aaea70ba6

Observation 6d395df3-d3f2-4dce-88e0-920eabc80a69 · outbound

This paper cites an unresolved cited work.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Unresolved cited work

Reference 88

Resolution
unresolved
raw_fallback, observed 2026-08-11T22:42:55.273178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:54.332332Z digest=sha256:6c546781d1ca7423a3469c5e8e5bc10ac9e194cddc02551e4a873e80a3f44603

Observation 2b7222f0-37fa-4f99-b2a5-68ba5b59e96d · outbound

This paper cites a black car viewed from behind on a street.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection a black car viewed from behind on a street

Reference 89

Resolution
malformed identifier
raw_fallback, observed 2026-08-11T22:42:55.253604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:54.338960Z digest=sha256:c71714148c8400d89dd794e7a60fcc2f45a58d5ba2c93859c61cf6ffff3170dc

Observation 232eaabc-dc06-47de-89f1-54293262a824 · outbound

This paper cites an unresolved cited work.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Unresolved cited work

Reference 90

Resolution
unresolved
raw_fallback, observed 2026-08-11T22:42:55.220328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T22:42:54.362361Z digest=sha256:30a601aa4cfc18097ee8c76e298d552297e55cdb9c5e8af73c5a8af775f22e10

Observation 09cdadc8-5e8d-4111-bacf-209a8e6eda34 · outbound

This paper cites an unresolved cited work.

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection Unresolved cited work

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-11T22:42:52.414751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:42:52.414751Z digest=sha256:f13150ef8263d1a0a53720269f57b5fe11e5b4ce794019bb62982bbe5432025e

Pith citing papers

No inbound Pith citation observations are available.