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Paper Citation Record · LEDGER

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

As of 7 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 2026-08-07T06:34:17.273281+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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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:03:09.294332Z digest=sha256:d3b5266f85681966c8b049422e3ea17254256bac6d0509b3a3b2a3b783bed2c1

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 2026-08-07T06:34:17.273281+00:00.

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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
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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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:03:09.413976Z digest=sha256:f94ab5674628da1a2778614a1cacdc12dbec75a064ccbf34230a2645691a41c4

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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verified exact
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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:03:09.497755Z digest=sha256:5c31dd4c1ee9ee67b322f5a86690a82d7959370c8d1233c4ce5d092896b357d8

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:03:09.569263Z digest=sha256:79d15b317036404caf8f3d000503548320aa457c123cbcd0d35a25e23bf9681f

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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raw_fallback, observed 2026-08-06T19:03:14.906345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:03:09.648348Z digest=sha256:cca319009c71123eb18acb160132019e4371ce26d5d5a65a77dfe4d80ec5d8b3

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:03:09.741240Z digest=sha256:4f3a7b0e5b027c8306ca9ff4039d0e11e983af90835ce2c7e5b3c75204efa854

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

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

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:03:09.869727Z digest=sha256:d0ee43d227e4ac53f0986584ac8a81c2d207d5d83b67e1bd9a0051b9419034f6

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:03:09.954295Z digest=sha256:713c562a70224f5ec620085f24d4670b242b520e0611aa578323d3b47b55f8b2

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:03:10.277548Z digest=sha256:bdb39cf5b098e7cfdb1806dc33d965dc4e0206959857009b6020aee82c535a4d

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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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:03:10.487100Z digest=sha256:014aca4d5a7ea85bb61cd6e4d9aa164e1b7a0f31e941b4f402d70d4417a2092d

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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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:03:10.652984Z digest=sha256:f6de7200cc0c04030e92645f3691f9c0d7221240d76eecb6192ac8fd6cebf3fa

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 2026-08-07T06:34:17.273281+00:00.

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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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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:03:10.903057Z digest=sha256:b0f10f07f6237d793dc1329f3068f48b994c5eadc248ed4ad75387ecbf160ad1

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

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:03:10.988247Z digest=sha256:c87fecb2fbcfa9f6ac5b3764bb0bd64ceab463572c50be6bd38ca1e775499839

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:03:11.064081Z digest=sha256:99a69c7ac544761f8863dff4d30e8bfe033e2157792c4f790724013940614a9b

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

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:03:11.138354Z digest=sha256:0fc153055d2eab7882ea6a4c384fa598a0376a223ab47c1170c19dd997bbbdca

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:03:11.205012Z digest=sha256:1702132959b19d7ccb7cde2bc9d10be98863d43f73ef53c02602f51fa66740b2

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:03:11.309790Z digest=sha256:af05dc346a7b9b2747357941a209d1da902ab3d8647aaae9c4761a710e516651

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:03:11.406433Z digest=sha256:d287ebaa1dc1dfb433a5192125edabfd253a11a7429a0356f46132a764a499c5

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:03:11.563217Z digest=sha256:4872d92dbda4b76429d1920492361b07577427023e7e0a76119fe47e5890ccd8

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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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

Unavailable: canonical work link unavailable.

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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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