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Paper Citation Record · LEDGER

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception

As of 8 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2507.06687.

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

pith.paper-citation-record.v1
2507.06687 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:03:12.933913Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

40 of 40 outbound references displayed

  • verified exact18
  • verified fuzzy6
  • unresolved15
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 90e10110-e03e-4790-8155-504f5079fcbe · outbound

This paper cites The Stixel World - A Compact Medium Level Representation of the 3D-World,.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception The Stixel World - A Compact Medium Level Representation of the 3D-World,

Reference 1

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doi, observed 2026-08-06T19:03:13.500083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 4dd7b530-40dc-4f78-9b02-12eb456dd12f · outbound

This paper cites The AEIF Data Collection: A Dataset for Infrastructure-Supported Perception Research with Focus on Public Transportation,.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception The AEIF Data Collection: A Dataset for Infrastructure-Supported Perception Research with Focus on Public Transportation,

Reference 2

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raw_fallback, observed 2026-08-06T19:03:14.869555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:03:09.294332Z digest=sha256:ccd9dfa776ae7d8b19b8ce094c16f7ec4fc33b860ed42d0802c8cc7138871373

Observation 516aa742-f6c4-4989-8725-26fb850c0290 · outbound

This paper cites StixelNExT: Toward Monocular Low-Weight Perception for Object Segmentation and Free Space Detection,.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception StixelNExT: Toward Monocular Low-Weight Perception for Object Segmentation and Free Space Detection,

Reference 3

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raw_fallback, observed 2026-08-06T19:03:14.798239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:03:09.366113Z digest=sha256:3600c67047361febe9caf138cfa12f06ce3955420391410a136abb8a91522885

Observation 5c0558c0-b669-47ae-831b-812ef9fa0688 · outbound

This paper cites Towards a Global Optimal Multi-Layer Stixel Representation of Dense 3D Data,.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception Towards a Global Optimal Multi-Layer Stixel Representation of Dense 3D Data,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:03:14.913300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:03:09.413976Z digest=sha256:3dbdbf11403c206374340c262bdee79a2e6ab55fa335667b6abb35a60b0fe955

Observation bd5d0b1c-28f1-4fcc-881c-cd6038ea3ff4 · outbound

This paper cites Semantic Stixels: Depth is not enough,.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception Semantic Stixels: Depth is not enough,

Reference 5

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raw_fallback, observed 2026-08-06T19:03:14.719924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:03:09.497755Z digest=sha256:94fbcd732c9bb0d11ac7d310b5e335984ecb19d176c473bf1996c1cf02d03d68

Observation 59512be4-a5f5-424c-8ca0-8ae248298d3e · outbound

This paper cites Instance Stixels: Segmenting and Grouping Stixels into Objects,.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception Instance Stixels: Segmenting and Grouping Stixels into Objects,

Reference 6

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raw_fallback, observed 2026-08-06T19:03:14.646185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:03:09.569263Z digest=sha256:648f9d9310a059a2cd554e90fac87fb36e933e1ad2ca571c0f14ed5c79049026

Observation f6866d5a-674b-4506-91ce-f1eea8ede548 · outbound

This paper cites StixelNet: A Deep Convolutional Network for Obstacle Detection and Road Segmentation,.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception StixelNet: A Deep Convolutional Network for Obstacle Detection and Road Segmentation,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:03:09.648348Z digest=sha256:c6075c9205bd3eed936c7dbfe34f92cfd775919c29da5007f28f609e18d9ef4c

Observation 1f37f341-64fc-4d48-95b4-165c68eb1a43 · outbound

This paper cites Real-Time Category- Based and General Obstacle Detection for Autonomous Driving,.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception Real-Time Category- Based and General Obstacle Detection for Autonomous Driving,

Reference 8

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raw_fallback, observed 2026-08-06T19:03:14.577232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:03:09.741240Z digest=sha256:65ee33655bf02f4f1b7ee696c34b19f15c961e2cd5eb1dab09e5ce29f8c7e10c

Observation 37836f17-e459-46ff-9b92-383c3ca1ccdf · outbound

This paper cites Mono-Stixels: Monocular depth reconstruction of dynamic street scenes.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception Mono-Stixels: Monocular depth reconstruction of dynamic street scenes

Reference 9

Resolution
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local_arxiv, observed 2026-08-06T19:03:14.485792Z

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Observation bdb2a323-4e1b-4a84-97f8-6228be36dfce · outbound

This paper cites Exploiting Single Image Depth Prediction for Mono-stixel Estimation,.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception Exploiting Single Image Depth Prediction for Mono-stixel Estimation,

Reference 10

Resolution
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doi, observed 2026-08-06T19:03:13.181365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:03:09.869727Z digest=sha256:831961984879144fef430e0984f0a87ef57785928e1cabe92c865854ede930c7

Observation aba5385b-fc50-40d5-b176-1146ed704cbc · outbound

This paper cites Unsupervised Monocular Depth Estimation with Left-Right Consistency,.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception Unsupervised Monocular Depth Estimation with Left-Right Consistency,

Reference 11

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raw_fallback, observed 2026-08-06T19:03:14.899159Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:03:09.954295Z digest=sha256:3ce7de1a4f3beebf2450ee8c4b7320ee4ea86350d8640171f89a507e138e49bb

Observation 62ecf9bc-591f-479e-bb2d-0d60479bda0e · outbound

This paper cites Digging Into Self-Supervised Monocular Depth Estimation.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception Digging Into Self-Supervised Monocular Depth Estimation

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:03:10.129567Z digest=sha256:f4c6e769046db0e68a352dc3645ea762835d11e0d8c210d1c4e444b06692463b

Observation 7f796b17-4330-4239-b65f-20fa3bcc3bca · outbound

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

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 13

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source=pdf_text observed=2026-08-06T19:03:10.196940Z digest=sha256:02dad7c9a61d8dea4ff4737c4a6fa94e2aacc305aca79dddfd090f15e498ae55

Observation e40cdcb8-d5ff-4d00-bef8-28979cbdc23f · outbound

This paper cites Depth Anything V2,.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception Depth Anything V2,

Reference 14

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:03:10.277548Z digest=sha256:fd41ee9816b4403ed0df026ff5c50a09ce30ea03f663b061c4443b3e9456bfea

Observation fb95f63c-1092-49d3-97e9-3c3b32c14bc7 · outbound

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

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception MonoScene: Monocular 3D Semantic Scene Completion

Reference 15

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:03:10.417954Z digest=sha256:e9dfe5710d15e005d703a2ec1d49558e29581dfe8c1bfe0e1c521bcf6b3a8e9d

Observation 628bc0ed-1ad3-4d66-9241-f830d95fdb78 · outbound

This paper cites Learning Occupancy for Monocular 3D Object Detection.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception Learning Occupancy for Monocular 3D Object Detection

Reference 16

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local_arxiv, observed 2026-08-06T19:03:14.435055Z

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source=pdf_text observed=2026-08-06T19:03:10.487100Z digest=sha256:418b39eeccda51211d3b505bdb3a7f5d1bda2491bfaab7532fd6fc3553ca17b6

Observation b12cd330-b73a-4490-869c-10acf423ae34 · outbound

This paper cites MonoGRNet: A Geometric Reasoning Network for Monocular 3D Object Localization.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception MonoGRNet: A Geometric Reasoning Network for Monocular 3D Object Localization

Reference 17

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local_arxiv, observed 2026-08-06T19:03:14.425214Z

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source=pdf_text observed=2026-08-06T19:03:10.575801Z digest=sha256:f5ca56ec15200d4b94807342fd4d18c2285143d1662dd68a1c4736336a6dce87

Observation 9fd72b2d-7fe1-4793-9cae-789375e232a7 · outbound

This paper cites You Only Look Bottom-Up for Monocular 3D Object Detection.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception You Only Look Bottom-Up for Monocular 3D Object Detection

Reference 18

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local_arxiv, observed 2026-08-06T19:03:14.414239Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:03:10.652984Z digest=sha256:22dfca80b2010259173dd1fe8d0eb12f48240736f38c02313b2343c31796e951

Observation e2eda1a9-b5b0-40e5-bc91-742ca2752f9a · outbound

This paper cites Translating Images into Maps.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception Translating Images into Maps

Reference 19

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local_arxiv, observed 2026-08-06T19:03:14.403757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:03:10.833228Z digest=sha256:9727e86bc3ffa3f488d7ab95a9374b2839af720dd697c378c81d911c2914e90d

Observation 625fd17c-3ade-4ea9-95b8-16811e295a75 · outbound

This paper cites SeaBird: Segmentation in Bird’s View with Dice Loss Improves Monocular 3D Detection of Large Objects,.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception SeaBird: Segmentation in Bird’s View with Dice Loss Improves Monocular 3D Detection of Large Objects,

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:03:10.903057Z digest=sha256:1f88f1f2ff4712e1290b0dc4cce8efbb3a05d60ff4760d563f7d6b029d343941

Observation fb920c05-bf22-4bf7-9972-fbbf8d52bb91 · outbound

This paper cites Enhancing 3D Object Detection with 2D Detection-Guided Query Anchors.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception Enhancing 3D Object Detection with 2D Detection-Guided Query Anchors

Reference 21

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local_arxiv, observed 2026-08-06T19:03:14.393526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:03:10.988247Z digest=sha256:f499073de7b2556787a6cdf01fcdf6c6346535f7f043574ea57fee0897f439d1

Observation e1235f63-0eaf-473e-963a-85b459d7e130 · outbound

This paper cites Estimating Depth From Monocular Images as Classification Using Deep Fully Convolutional Residual Networks,.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception Estimating Depth From Monocular Images as Classification Using Deep Fully Convolutional Residual Networks,

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:03:11.064081Z digest=sha256:0b09395458818a4efacb4e03e66957a4b4b3148681b01f673383dd09363dce60

Observation 4f19a439-b83f-461c-81e0-e9801a544e44 · outbound

This paper cites Pseudo-LiDAR From Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving,.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception Pseudo-LiDAR From Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving,

Reference 23

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raw_fallback, observed 2026-08-06T19:03:14.322618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:03:11.138354Z digest=sha256:ebd63698a36f7c36083f0d9b46a05a8e9e369758fde081a4a429cf8dc9be7b5f

Observation bf99724e-e5de-4fb3-bf85-afffa3947b84 · outbound

This paper cites CAM-Convs: Camera-Aware Multi-Scale Convolutions for Single-View Depth.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception CAM-Convs: Camera-Aware Multi-Scale Convolutions for Single-View Depth

Reference 24

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local_arxiv, observed 2026-08-06T19:03:14.262352Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:03:11.205012Z digest=sha256:d14364486da13ca0cd1822305d852a814fdb63c0eb53e5949da415440d79ded2

Observation e20e83fc-db50-4822-a1cd-7b482e35491e · outbound

This paper cites Learning Depth from Single Images with Deep Neural Network Embedding Focal Length.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception Learning Depth from Single Images with Deep Neural Network Embedding Focal Length

Reference 25

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local_arxiv, observed 2026-08-06T19:03:14.251338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:03:11.309790Z digest=sha256:2f1544d2049200dfe34ff5a8d4e627894a7296f0df489734e12b248c33991fd2

Observation 83e9145d-e30c-4845-853b-2d7e3c7b9805 · outbound

This paper cites Patchwork++: Fast and Robust Ground Segmentation Solving Partial Under-Segmentation Using 3D Point Cloud,.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception Patchwork++: Fast and Robust Ground Segmentation Solving Partial Under-Segmentation Using 3D Point Cloud,

Reference 26

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raw_fallback, observed 2026-08-06T19:03:14.048991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:03:11.406433Z digest=sha256:53755c5d72a6718b972aaa1edc3207a110a7179146001cdf6b5857bff7a3b1ba

Observation 9d771b6d-f481-40e7-84cf-b33cb4af27b5 · outbound

This paper cites A ConvNet for the 2020s.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception A ConvNet for the 2020s

Reference 27

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T19:03:11.481155Z digest=sha256:9906912b463d47096cae89a56ba1d684c48d0d7f85135990c993dfb8a8afc952

Observation d4855c8e-2ce2-4ee6-a4ac-d20100adddd8 · outbound

This paper cites Hartley and A.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception Hartley and A

Reference 28

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raw_fallback, observed 2026-08-06T19:03:14.876685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:03:11.563217Z digest=sha256:1bef4064f7fc2938f975b39d5d5c78fffbd855cb93ae55c7cccd0e19977a1487

Observation 89fdc2d9-2465-489c-aa35-0db7f0d22418 · outbound

This paper cites Scalability in Perception for Autonomous Driving: Waymo Open Dataset.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception Scalability in Perception for Autonomous Driving: Waymo Open Dataset

Reference 29

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no resolver link, observed 2026-08-06T19:03:11.593133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:03:11.593133Z digest=sha256:a1b325699b1f32964c6de0d6a259bdb3909e372a9274cc29375f3f783c3f87fd

Observation 57e63167-52b8-4157-8446-9a4c7e99de75 · outbound

This paper cites LET-3D-AP: Longitudinal Error Tolerant 3D Average Precision for Camera-Only 3D Detection.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception LET-3D-AP: Longitudinal Error Tolerant 3D Average Precision for Camera-Only 3D Detection

Reference 30

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no resolver link, observed 2026-08-06T19:03:11.663731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:03:11.663731Z digest=sha256:8bdaa1c8d689a6aaea1039e950a78228746f6e424d3b9f16ca3b433ab01e5c0a

Observation 419b70d6-a265-4877-b208-bab3e1f686f3 · outbound

This paper cites Are we ready for autonomous driving? The KITTI vision benchmark suite,.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception Are we ready for autonomous driving? The KITTI vision benchmark suite,

Reference 31

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:03:11.854501Z digest=sha256:1572801b5b8357d1b2ca8e26c1d256a5ab485899d4eac9bbfc9617104453980a

Observation 597088ce-675c-4c40-90c4-5894ca8aa5c9 · outbound

This paper cites Probabilistic and Geometric Depth: Detecting Objects in Perspective.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception Probabilistic and Geometric Depth: Detecting Objects in Perspective

Reference 32

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:03:12.007827Z digest=sha256:bdf8f1bd8df87ecc5b7017e6285606d161ebbad0c543531007687bf0b912a0e9

Observation 1315b551-ee4a-4ef4-8bb7-84d5b75cf0a9 · outbound

This paper cites The Pascal Visual Object Classes Challenge: A Retrospective,.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception The Pascal Visual Object Classes Challenge: A Retrospective,

Reference 33

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no resolver link, observed 2026-08-06T19:03:12.207041Z

Source-reported events for the cited work

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Observation 16340daa-e2be-4f96-b20e-cf644f51a53d · outbound

This paper cites EfficientNetV2: Smaller Models and Faster Training.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception EfficientNetV2: Smaller Models and Faster Training

Reference 34

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Observation 220cab35-4ea2-4dbe-8b98-5ad572a68761 · outbound

This paper cites Searching for MobileNetV3.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception Searching for MobileNetV3

Reference 35

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Observation 5f12e28f-e63b-4a86-aad5-e32549a41d18 · outbound

This paper cites ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design

Reference 36

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Observation f4e376cc-2d94-443f-a733-0b8fff9d5d28 · outbound

This paper cites Swin Transformer: Hierarchical Vision Transformer using Shifted Windows.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception Swin Transformer: Hierarchical Vision Transformer using Shifted Windows

Reference 37

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Observation 769467a0-083f-428c-b36e-0770f2855011 · outbound

This paper cites Attention Is All You Need.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception Attention Is All You Need

Reference 38

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Observation d152aa18-e1e2-4c3f-96b8-f4e4acdbc324 · outbound

This paper cites Unsupervised Monocular Depth Estimation with Left-Right Consistency.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception Unsupervised Monocular Depth Estimation with Left-Right Consistency

Reference 2016

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Observation 07468896-3aad-4367-a6b7-06bef8b499a4 · outbound

This paper cites Depth Anything V2.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception Depth Anything V2

Reference 2024

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Pith citing papers

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