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Paper Citation Record · LEDGER

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction

As of 13 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 2 inbound Pith citation observations for arXiv:2412.11210.

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

pith.paper-citation-record.v1
2412.11210 v2

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T15:14:05.016060Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-15T10:49:28.959330Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T14:08:22.645266Z

Reference resolution

42 of 42 outbound references displayed

  • verified exact0
  • verified fuzzy36
  • unresolved5
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 383dadf1-89b8-418c-a874-4544d5805305 · outbound

This paper cites Unsupervised Scale-Consistent Depth and Ego-Motion Learning from Monocular Video.Advances in Neural Information Processing Systems (NeurIPS) , 32,.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction Unsupervised Scale-Consistent Depth and Ego-Motion Learning from Monocular Video.Advances in Neural Information Processing Systems (NeurIPS) , 32,

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 1d5fb942-73b5-4481-b9fa-8ed9de002316 · outbound

This paper cites MonoScene: Monocular 3D Semantic Scene Completion.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction MonoScene: Monocular 3D Semantic Scene Completion

Reference 2

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 507c5887-5654-47fe-9aef-b5a702045d12 · outbound

This paper cites Self-Supervised Monocular Depth Esti- mation: Solving the Edge-Fattening Problem.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction Self-Supervised Monocular Depth Esti- mation: Solving the Edge-Fattening Problem

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 828bf54d-0621-4c2f-b07b-619e0429be7c · outbound

This paper cites The Cityscapes Dataset for Semantic Ur- ban Scene Understanding.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction The Cityscapes Dataset for Semantic Ur- ban Scene Understanding

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 9d88cb73-3b2a-4666-94ea-397c63b2fe66 · outbound

This paper cites ImageNet: A large-scale hierarchical im- age database.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction ImageNet: A large-scale hierarchical im- age database

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation a25db425-2587-4117-97f4-2a19571dc478 · outbound

This paper cites Vision Meets Robotics: the KITTI Dataset.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction Vision Meets Robotics: the KITTI Dataset

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 8bdf8e45-1769-40c5-85e5-3f60f88d354c · outbound

This paper cites Digging into Self-Supervised Monoc- ular Depth Estimation.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction Digging into Self-Supervised Monoc- ular Depth Estimation

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 623dbdfe-8990-493f-ae4e-d810185188c0 · outbound

This paper cites 3D Packing for Self-Supervised Monocular Depth Estimation.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction 3D Packing for Self-Supervised Monocular Depth Estimation

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T15:14:04.800140Z digest=sha256:d98576c916a79a5222785d08c3f566d98756d0fd99fc6853c681851c6eb80196

Observation 03dfcf2e-c253-42cd-bfc8-f1cbaa0e7302 · outbound

This paper cites Semantically-Guided Representation Learning for Self-Supervised Monocular Depth.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction Semantically-Guided Representation Learning for Self-Supervised Monocular Depth

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:14:04.805243Z digest=sha256:41ec1e4aba0b356d7c73cc2e98a997c4b48298fd9001feb8bf3b2dd6787b676e

Observation afee6274-9f2a-49e0-9890-e498bbe52152 · outbound

This paper cites Boosting Self-Supervision for Single- View Scene Completion via Knowledge Distillation.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction Boosting Self-Supervision for Single- View Scene Completion via Knowledge Distillation

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation e64153ca-8f24-48d2-bf0c-942f722efdf7 · outbound

This paper cites Deep Residual Learning for Image Recog- nition.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction Deep Residual Learning for Image Recog- nition

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T15:14:04.819157Z digest=sha256:6684c187e7537c289e2e8f5fdb8df5f0d625fa3eac743c7e3261b9b82c402a89

Observation 4c187b64-dc8e-462c-be4e-2d90ea5e22c0 · outbound

This paper cites Tri-Perspective View for Vision- Based 3D Semantic Occupancy Prediction.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction Tri-Perspective View for Vision- Based 3D Semantic Occupancy Prediction

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T15:14:04.825967Z digest=sha256:bc3c3e255c7ab8900a0ebcb902fda4dd8aafae207664767927d3a31ec3e2f0c8

Observation b4288378-f893-4ef7-bb9a-4af97d91370e · outbound

This paper cites SelfOcc: Self-Supervised Vision- Based 3D Occupancy Prediction.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction SelfOcc: Self-Supervised Vision- Based 3D Occupancy Prediction

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T15:14:04.835149Z digest=sha256:3ff15d52c2efbb9fe865aced2f22a9161d2a9e5d7e9c2e2d7bb6f22a357b453c

Observation 73d5e894-4dd9-425e-aa45-482620d1edfd · outbound

This paper cites Fine-Grained Semantics-Aware Representation Enhancement for Self-Supervised Monocu- lar Depth Estimation.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction Fine-Grained Semantics-Aware Representation Enhancement for Self-Supervised Monocu- lar Depth Estimation

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T15:14:04.839617Z digest=sha256:c13bf69b2b9c248cc7560a6b4cb6eb509b4f6fad55e3fa21485d00e8fc40b0ff

Observation 950ec73f-dbf5-479b-b456-50ac1482a5cb · outbound

This paper cites LERF: Language Embedded Radiance Fields.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction LERF: Language Embedded Radiance Fields

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 5dc71dc9-8739-4c5e-804f-f6477c920d5e · outbound

This paper cites Segment Anything.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction Segment Anything

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T15:14:04.850788Z digest=sha256:6fe3598f3da54868bc2f5e61ebc1d656ca48bf64b76548bfd8190c64ac142136

Observation fbae4a32-baca-4080-b738-644b3665ba3d · outbound

This paper cites Depth Anything V2.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction Depth Anything V2

Reference 17

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:14:04.855807Z digest=sha256:665b9356016f3f8a72d0ab771c54e47f6999d47c3659a419834d30bc7e495390

Observation 3c3a6df3-86a9-4195-8d04-5b46ef947b32 · outbound

This paper cites Know Your Neighbors: Improving Single- View Reconstruction via Spatial Vision-Language Reason- ing.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction Know Your Neighbors: Improving Single- View Reconstruction via Spatial Vision-Language Reason- ing

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation b2c4d5ab-96e3-40ce-9420-a579e5b3644d · outbound

This paper cites KITTI-360: A Novel Dataset and Bench- marks for Urban Scene Understanding in 2D and 3D.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction KITTI-360: A Novel Dataset and Bench- marks for Urban Scene Understanding in 2D and 3D

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T15:14:04.867019Z digest=sha256:c61284cc9334404fdddba4613fd98f48829e11040e14227bd59474cb3f7b9eee

Observation 149737aa-7f49-4e75-af71-90b8bc0d5bf0 · outbound

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

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T15:14:04.879525Z digest=sha256:a3b634b23c75aa7e581da0567ab2979e055e49888f2a97079c16b3d18e48dc06

Observation 32f5e122-33fd-4b1e-846e-81826614309e · outbound

This paper cites OpenScene: 3D Scene Understanding with Open V ocabularies.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction OpenScene: 3D Scene Understanding with Open V ocabularies

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T15:14:04.884307Z digest=sha256:094e665bb5fb60173221d12247faeb38d60db9e3ff0cc069e57c315f4aea6b15

Observation ff5c56d5-730a-4b61-92fc-cc430c418957 · outbound

This paper cites Grounded SAM: Assembling Open-World Models for Diverse Visual Tasks.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction Grounded SAM: Assembling Open-World Models for Diverse Visual Tasks

Reference 22

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:14:04.889131Z digest=sha256:1ff52c7069d52f3b10b8c795cf1ff4caf64257e001f8dd4693e91299aeb72a3a

Observation 52e71ed8-71a9-4a71-af90-d60f8d446dde · outbound

This paper cites R3D3: Dense 3D Reconstruction of Dynamic Scenes from Multiple Cameras.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction R3D3: Dense 3D Reconstruction of Dynamic Scenes from Multiple Cameras

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T15:14:04.894219Z digest=sha256:f291f97f759c78a31d4fa377ec97b9557801687338b7339264f2956670f7e40d

Observation 52acc328-5195-4c7f-bb5d-722de6b7dc2f · outbound

This paper cites SwinDepth: Unsuper- vised Depth Estimation Using Monocular Sequences via Swin Transformer and Densely Cascaded Network.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction SwinDepth: Unsuper- vised Depth Estimation Using Monocular Sequences via Swin Transformer and Densely Cascaded Network

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T15:14:04.904046Z digest=sha256:5bdbe0ee53262419f30ee05774572363199b65e74932eafb2e9543ce8388ec7c

Observation 345d6de2-6513-49f9-8f46-7fd03da93e34 · outbound

This paper cites SC-DepthV3: Robust Self-Supervised Monocular Depth Estimation for Dynamic Scenes.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction SC-DepthV3: Robust Self-Supervised Monocular Depth Estimation for Dynamic Scenes

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T15:14:04.908920Z digest=sha256:cd1f8a0a8c0fbf8e029bd445ee66cd6c63b0e30d1a4b4ba457cf762ee839a2ae

Observation 8ce26d9f-4b8f-4d90-b913-77a032e619ae · outbound

This paper cites Dynamo-Depth: Fixing Unsupervised Depth Estimation for Dynamical Scenes.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction Dynamo-Depth: Fixing Unsupervised Depth Estimation for Dynamical Scenes

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T15:14:04.913812Z digest=sha256:ed2e8a73cca9c400f1021cdeac017cf27417961ea1d30de5547171928beccf27

Observation 048263ec-d8ac-4416-8ebc-e464a43b1a78 · outbound

This paper cites Occ3D: A large-scale 3d occupancy pre- diction benchmark for autonomous driving.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction Occ3D: A large-scale 3d occupancy pre- diction benchmark for autonomous driving

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T15:14:04.918926Z digest=sha256:42e5c010c0ff7e7950f342803769e26159c2f5f0d050e76b592e307fbc1fd911

Observation c0b6a51c-4045-482a-8f2a-dee95fddf3e3 · outbound

This paper cites InternImage: Exploring Large-Scale Vi- sion Foundation Models with Deformable Convolutions.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction InternImage: Exploring Large-Scale Vi- sion Foundation Models with Deformable Convolutions

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T15:14:04.924323Z digest=sha256:730741872d8a40f59d9c354397ed4e093a7b8948e4b584725f5538435748f64d

Observation 6069beed-6421-402b-b7d4-362034b350ef · outbound

This paper cites SQLdepth: Generalizable Self- Supervised Fine-Structured Monocular Depth Estimation.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction SQLdepth: Generalizable Self- Supervised Fine-Structured Monocular Depth Estimation

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T15:14:04.930391Z digest=sha256:458e73def3e594224e41fee18ef324c9a697815d1fd77cdffb2fc26d41104eee

Observation ce09b5b1-21a3-4634-84f2-4c9a7e2ea98f · outbound

This paper cites The Temporal Opportunist: Self- Supervised Multi-Frame Monocular Depth.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction The Temporal Opportunist: Self- Supervised Multi-Frame Monocular Depth

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T15:14:04.936755Z digest=sha256:306413b73d12955f0a8031b76916132c112802747ed3d92a86de191107565e0f

Observation 5da6d643-9469-4db3-b18d-769e4eccc918 · outbound

This paper cites SurroundOcc: Multi-Camera 3D Occupancy Prediction for Autonomous Driving.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction SurroundOcc: Multi-Camera 3D Occupancy Prediction for Autonomous Driving

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T15:14:04.942740Z digest=sha256:240abf1d86aee91140442c7469a9f1e793ac89d8c0e0b9627372722ec09f0839

Observation 2974ad1a-bc81-4931-9d9d-2d1b32ce4f0e · outbound

This paper cites Behind the Scenes: Density Fields for Single View Reconstruction.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction Behind the Scenes: Density Fields for Single View Reconstruction

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:14:05.543067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T15:14:04.952016Z digest=sha256:4daf80a96a39f3bdebcea77a9ee24c410af3f2ac8e4be1b1523a65766c496ddd

Observation b339f777-a486-4f05-9a4d-9a6adba28086 · outbound

This paper cites Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:14:05.498280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T15:14:04.957182Z digest=sha256:996d31139814556e5b131450d13d8d7cab60eae3fe6118d482f6a022282b0ce6

Observation 6bab17d8-a746-488d-830d-e63ded73274f · outbound

This paper cites Learning to Recover 3D Scene Shape from a Single Image.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction Learning to Recover 3D Scene Shape from a Single Image

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:14:05.474054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T15:14:04.961946Z digest=sha256:6309c586ae25519a46b281816d8bffe03aac0109d95d0e32e585f8388df86183

Observation fac9fe48-b630-4433-95a1-7f73d15b8b8e · outbound

This paper cites GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:14:05.450814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T15:14:04.968525Z digest=sha256:1295cff81ceea81f2aab060f011c46a843e638f03887a3a7f3e829ecbaada845

Observation 3032c79d-b99d-4ae3-b885-27e52f8a3c80 · outbound

This paper cites PixelNeRF: Neural Radiance Fields from One or Few Images.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction PixelNeRF: Neural Radiance Fields from One or Few Images

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:14:05.414425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T15:14:04.977170Z digest=sha256:e0c0fe94dbff6d684362ad720517ea08c8ed74325a36941877bf1829e9583456

Observation dc334caf-654e-4fb7-8939-19c4e735fd66 · outbound

This paper cites OccNeRF: Advancing 3D Occupancy Prediction in LiDAR-Free Environments.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction OccNeRF: Advancing 3D Occupancy Prediction in LiDAR-Free Environments

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-11T15:14:04.984044Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:14:04.984044Z digest=sha256:6d9c823b3c9b4122edbf6f6d1d10dfbf1fcf5cf8187bb08264cd9b843da17a53

Observation bcd080bb-726a-4685-bf65-bcb02e96611a · outbound

This paper cites Lite-Mono: a Lightweight CNN and Transformer Architecture for Self-Supervised Monocular Depth Estimation.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction Lite-Mono: a Lightweight CNN and Transformer Architecture for Self-Supervised Monocular Depth Estimation

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:14:05.386201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T15:14:04.989515Z digest=sha256:c3a8a2c499556a7f14d9cee38a1c10913a872e6827039fd247d87f5ba3918d8f

Observation e380db5f-84ed-4926-994e-725929123f2a · outbound

This paper cites Vision-based 3D occupancy prediction in autonomous driving: a review and outlook.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction Vision-based 3D occupancy prediction in autonomous driving: a review and outlook

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-11T15:14:04.994318Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:14:04.994318Z digest=sha256:0c13f7dabcb7f0e3cc0b23a251d2079ef4e89ea13b18ac6a1010dbeacdde90a7

Observation 68f47aec-3bcb-404d-9341-53989d01d523 · outbound

This paper cites MonoOcc: Digging into Monocu- lar Semantic Occupancy Prediction.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction MonoOcc: Digging into Monocu- lar Semantic Occupancy Prediction

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:14:05.353980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T15:14:05.000448Z digest=sha256:e2652e7aecacb7df952811c61b5dc1fab474b117a6ba793748768fa0b4116708

Observation e781505e-ec56-49c6-960e-2b15a7155ae6 · outbound

This paper cites bridge” and “tunnel.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction bridge” and “tunnel

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:14:05.271796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T15:14:05.005232Z digest=sha256:c6092676ef4fbb5050c14067f98625dbf718c33955aa1c78129bca03c15d8c98

Observation d96982f8-4f84-4080-8d39-3a86f2bf47cd · outbound

This paper cites The stereo image pairs with adjacent timestamps are fed into the network for image ren- dering and photometric reconstruction.

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction The stereo image pairs with adjacent timestamps are fed into the network for image ren- dering and photometric reconstruction

Reference 42

Resolution
malformed identifier
raw_fallback, observed 2026-08-11T15:14:05.193349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T15:14:05.016060Z digest=sha256:c34346942078e0bccf1bf9dbaf293ea5ba8b46d52556fff7b2f9941acd7fe673

Pith citing papers

Observation 5fa41f78-919d-4190-9299-043c2ded2ed0 · inbound

VISA: VLM-Guided Instance Semantic Auditing for 3D Occupancy World Models cites this paper.

VISA: VLM-Guided Instance Semantic Auditing for 3D Occupancy World Models ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-07-03T14:08:22.646606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-06-27T07:08:41.071757Z digest=sha256:5908424252e101df1cb8c6f05ad9ca16d39c157e43aa5266fd62f2a8b1a58ee3

Observation c8a91825-72fe-4f8a-8cd5-55ac035ccb32 · inbound

VISA: VLM-Guided Instance Semantic Auditing for 3D Occupancy World Models cites this paper.

VISA: VLM-Guided Instance Semantic Auditing for 3D Occupancy World Models ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction

Reference 34

Resolution
unresolved
no resolver link, observed 2026-07-15T10:49:28.959330Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-15T10:49:28.959330Z digest=sha256:5c4def0b6dbec582ef2ed226afa0e8d4177bb95b005d6dfcb0b151fbda0d6293