Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-01T00:42:18.946960Z
Paper Citation Record · LEDGER
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving
As of 10 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 0 inbound Pith citation observations for arXiv:2607.26165.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
53 of 53 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved53
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation e7ccd08f-aff5-42c9-a71d-308baea03215 · outbound
This paper cites 4d- former: Multimodal4dpanopticsegmentation.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving 4d- former: Multimodal4dpanopticsegmentation
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:12.340325Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 104618e0-fb02-4666-a630-761f020b105b · outbound
This paper cites Fantrack: 3d multi- object tracking with feature association network.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Fantrack: 3d multi- object tracking with feature association network
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:12.527156Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4681906b-0448-4861-9c19-3fcb07ab9b5d · outbound
This paper cites Semantickitti: Adatasetforsemanticsceneunderstandingoflidarsequences.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Semantickitti: Adatasetforsemanticsceneunderstandingoflidarsequences
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:12.646018Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 71b037a6-349a-4251-8dea-ab7f7f59526f · outbound
This paper cites Depth Pro: Sharp Monocular Metric Depth in Less Than a Second.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Depth Pro: Sharp Monocular Metric Depth in Less Than a Second
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:12.732955Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b88df963-0bb5-4e06-b6dd-88cb9b7385bd · outbound
This paper cites Cafuser: Condition-aware multimodal fusion for robust semantic perception of driving scenes.IEEE Robotics and Automation Letters, 2025.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Cafuser: Condition-aware multimodal fusion for robust semantic perception of driving scenes.IEEE Robotics and Automation Letters, 2025
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:12.846763Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5fe7c361-e909-487e-a23f-343f72140029 · outbound
This paper cites Dgfusion: Depth-guidedsensor fusion for robust semantic perception.IEEE Robotics and Automation Letters, 2026.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Dgfusion: Depth-guidedsensor fusion for robust semantic perception.IEEE Robotics and Automation Letters, 2026
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:12.929231Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 629f1746-cd28-40d7-b325-81a6fd4a21a3 · outbound
This paper cites End- to-end object detection with transformers.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving End- to-end object detection with transformers
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:13.015093Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d3c08c3a-227a-4d94-8377-117a89f3abf8 · outbound
This paper cites Panoptic-deeplab: A simple, strong, and fast baseline for bottom-up panoptic segmentation.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Panoptic-deeplab: A simple, strong, and fast baseline for bottom-up panoptic segmentation
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:13.092641Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ed09b1b6-ba50-4dd9-8216-f56560a16bdf · outbound
This paper cites Per- pixel classification is not all you need for semantic segmenta- tion.NeurIPS, 2021.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Per- pixel classification is not all you need for semantic segmenta- tion.NeurIPS, 2021
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:13.220990Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fa649f8e-6a73-4c72-b738-e879719cd41b · outbound
This paper cites Masked-attention mask trans- former for universal image segmentation.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Masked-attention mask trans- former for universal image segmentation
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:13.317526Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f98af75d-6873-4062-836c-1b15b4df02b1 · outbound
This paper cites The cityscapes dataset for semantic urban scene understanding.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving The cityscapes dataset for semantic urban scene understanding
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:13.437414Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b3608c8c-175d-462d-82b4-f35ef0a80e3e · outbound
This paper cites Depth map prediction from a single image using a multi-scale deep network.NeurIPS, 2014.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Depth map prediction from a single image using a multi-scale deep network.NeurIPS, 2014
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:13.572993Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dd13ff7d-249f-414e-af9d-84530f8b9109 · outbound
This paper cites Cc-3dt: Panoramic 3d object tracking via cross-camera fusion.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Cc-3dt: Panoramic 3d object tracking via cross-camera fusion
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:13.732609Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e1ae02ae-b5a1-4ab0-b36f-ebbc8ec46178 · outbound
This paper cites Qdtrack: Quasi-dense similarity learning for appearance-only multiple object tracking.T-PAMI, 2023.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Qdtrack: Quasi-dense similarity learning for appearance-only multiple object tracking.T-PAMI, 2023
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:13.849629Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 960e1f45-239a-41d6-837d-0e2c8ea603c3 · outbound
This paper cites Panopticdepth: A unified framework for depth-aware panoptic segmentation.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Panopticdepth: A unified framework for depth-aware panoptic segmentation
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:13.979899Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a8688b36-f9f4-42ee-95ac-5256b4719041 · outbound
This paper cites Are we ready for autonomous driving? the kitti vision benchmark suite.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Are we ready for autonomous driving? the kitti vision benchmark suite
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:14.131099Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ee891143-37ae-460c-b955-a994e7d9964f · outbound
This paper cites Deep residual learning for image recognition.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Deep residual learning for image recognition
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:14.249643Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e09c0a94-d6d7-4491-abb4-c6d3c7b3336a · outbound
This paper cites Mask r-cnn.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Mask r-cnn
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:14.371272Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ac62a910-2d62-4214-8434-af1965080a1a · outbound
This paper cites Monocular quasi-dense 3d object tracking.T-PAMI, 2022.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Monocular quasi-dense 3d object tracking.T-PAMI, 2022
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:14.482458Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9b2b050f-b9f5-413c-a2a6-c0c3d1ac6d16 · outbound
This paper cites Metric3Dv2: A Versatile Monocular Geometric Foundation Model for Zero-shot Metric Depth and Surface Normal Estimation.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Metric3Dv2: A Versatile Monocular Geometric Foundation Model for Zero-shot Metric Depth and Surface Normal Estimation
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:14.580703Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 908a1ca5-c0cb-4a33-ba70-b24d52d36ea3 · outbound
This paper cites Computervisionforautonomousvehicles: Problems,datasets and state of the art.Foundations and Trends in Computer Graphics and Vision, 2020.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Computervisionforautonomousvehicles: Problems,datasets and state of the art.Foundations and Trends in Computer Graphics and Vision, 2020
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:14.683074Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e9c382c9-3b29-4fd9-957c-c8f22434f144 · outbound
This paper cites Uni-dvps: Unified model for depth-aware video panoptic segmentation.IEEE Robotics and Automation Letters (RA-L), 2024.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Uni-dvps: Unified model for depth-aware video panoptic segmentation.IEEE Robotics and Automation Letters (RA-L), 2024
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:14.827936Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 706ed449-0b74-440f-bedc-c7ff67cfaa87 · outbound
This paper cites Eager- mot: 3d multi-object tracking via sensor fusion.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Eager- mot: 3d multi-object tracking via sensor fusion
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:14.948355Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6a4c67a3-c4d8-4f08-8bc9-18acce1cdb1e · outbound
This paper cites Video panoptic segmentation.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Video panoptic segmentation
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:15.051868Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8431cba7-3505-4bdb-a304-172903e9ff65 · outbound
This paper cites Semantic hierarchy- guided adversarial attack for autonomous driving.IEEE Robotics and Automation Letters, 2025.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Semantic hierarchy- guided adversarial attack for autonomous driving.IEEE Robotics and Automation Letters, 2025
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:15.163731Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8341df67-c676-41e0-a713-ee6993ec9b67 · outbound
This paper cites Adam: A Method for Stochastic Optimization.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Adam: A Method for Stochastic Optimization
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:15.295980Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f48d9ef6-f1ea-47ae-a219-83e789ac39cb · outbound
This paper cites Panoptic segmentation.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Panoptic segmentation
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:15.421111Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e568084a-fe54-43f9-9f0f-94df7f8424d1 · outbound
This paper cites Tracking every thing in the wild.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Tracking every thing in the wild
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:15.527147Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4f88d586-dfdb-43c8-a296-fa7bb61e904e · outbound
This paper cites Fully convolutional networks for panoptic segmentation.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Fully convolutional networks for panoptic segmentation
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:15.680623Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9a44bc0b-ebf6-45ca-9821-1e8abe654c5c · outbound
This paper cites Object-centric learning with slot attention.NeurIPS, 2020.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Object-centric learning with slot attention.NeurIPS, 2020
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:15.765626Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ca56e4c1-4b4e-43a2-a8a3-495f03dbff13 · outbound
This paper cites V-net: Fully convolutional neural networks for volumetric medical image segmentation.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving V-net: Fully convolutional neural networks for volumetric medical image segmentation
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:15.918797Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation feee1c56-af29-4f56-9ff4-d0d72290ba51 · outbound
This paper cites Scalableparallelprogrammingwithcuda: Iscudatheparallel programming model that application developers have been waiting for?Queue, 2008.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Scalableparallelprogrammingwithcuda: Iscudatheparallel programming model that application developers have been waiting for?Queue, 2008
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:16.083115Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fda85996-07a7-4c75-a718-5b0e6a2891a3 · outbound
This paper cites Quasi-densesimilaritylearning for multiple object tracking.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Quasi-densesimilaritylearning for multiple object tracking
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:16.194823Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d6833738-aafc-4a96-9d09-277767362d76 · outbound
This paper cites Pytorch: An imperative style, high-performance deep learning library.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Pytorch: An imperative style, high-performance deep learning library
Reference 34
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:16.278313Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1503eff7-081c-4f87-97a2-9e3ad3468d18 · outbound
This paper cites Monodvps: A self- supervised monocular depth estimation approach to depth- aware video panoptic segmentation.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Monodvps: A self- supervised monocular depth estimation approach to depth- aware video panoptic segmentation
Reference 35
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:16.332266Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f7cfccde-ae7d-4baa-8e71-7ba4a56028a7 · outbound
This paper cites iDisc: Internal discretization for monocular depth estimation.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving iDisc: Internal discretization for monocular depth estimation
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:16.456776Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 62dd0c55-fbfc-44ff-a448-6c31f5cfd08c · outbound
This paper cites Unidepth: Universalmonocularmetricdepthestimation.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Unidepth: Universalmonocularmetricdepthestimation
Reference 37
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:16.624983Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8c48bafa-9ab5-46c8-8313-1e0d22ec9e4f · outbound
This paper cites UniK3D: Universal camera monocular 3d estimation.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving UniK3D: Universal camera monocular 3d estimation
Reference 38
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:16.780312Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 51b98ed6-641b-4035-800e-6ec707d18ad2 · outbound
This paper cites UniDepthV2: Universal Monocular Metric Depth Estimation Made Simpler.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving UniDepthV2: Universal Monocular Metric Depth Estimation Made Simpler
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:16.905682Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7b484f29-e729-4d61-928a-6ef8792299da · outbound
This paper cites Vip-deeplab: Learning visual perception with depth-aware video panoptic segmentation.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Vip-deeplab: Learning visual perception with depth-aware video panoptic segmentation
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:17.049244Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ee4e7d8d-d202-4261-827d-4149869d6212 · outbound
This paper cites Balancing shared and task-specific repre- sentations: A hybrid approach to depth-aware video panoptic segmentation.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Balancing shared and task-specific repre- sentations: A hybrid approach to depth-aware video panoptic segmentation
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:17.161756Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8d3b4382-3177-48ea-a81c-b23bf2d8ebf0 · outbound
This paper cites Attention is all you need.NeurIPS, 2017.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Attention is all you need.NeurIPS, 2017
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:17.333005Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9d3aec89-b23d-43b0-8de2-21731a8a6b80 · outbound
This paper cites A good foundation is worth many labels: Label-efficient panoptic segmentation.IEEE Robotics and Automation Letters, 2024.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving A good foundation is worth many labels: Label-efficient panoptic segmentation.IEEE Robotics and Automation Letters, 2024
Reference 43
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:17.471014Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f19527a7-311e-4bcb-a0d1-55161b116b22 · outbound
This paper cites Fastdepth: Fast monocular depth estima- tion on embedded systems.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Fastdepth: Fast monocular depth estima- tion on embedded systems
Reference 44
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:17.532621Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6aac35ad-b1e8-41e2-9f6c-cf3e0ea24ad3 · outbound
This paper cites In defense of online models for video instance segmentation.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving In defense of online models for video instance segmentation
Reference 45
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:17.666799Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 36c0de05-086d-4ea1-9572-a9628beffedb · outbound
This paper cites Efficientdps: Efficient and end-to-end depth- aware panoptic segmentation.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Efficientdps: Efficient and end-to-end depth- aware panoptic segmentation
Reference 46
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:17.813541Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9f0c65ef-85af-4c6b-b49c-27882d5a1ff7 · outbound
This paper cites Upsnet: A unified panoptic segmentation network.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Upsnet: A unified panoptic segmentation network
Reference 47
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:17.962081Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d7ce6714-b229-42fa-828b-bdd56d5bb18d · outbound
This paper cites Video instance segmentation.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Video instance segmentation
Reference 48
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:18.117289Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b852eabf-9494-4d1d-819d-41e6d6a226a4 · outbound
This paper cites k-means mask transformer.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving k-means mask transformer
Reference 49
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:18.283690Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ef991ac2-7bc2-4b88-ba55-81b24f328dd9 · outbound
This paper cites Polyphonicformer: unified query learning for depth-aware video panoptic segmentation.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Polyphonicformer: unified query learning for depth-aware video panoptic segmentation
Reference 50
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:18.447856Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1b2a043c-89a2-45c6-9528-409005f74570 · outbound
This paper cites K-net: Towards unified image segmentation.NeurIPS,.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving K-net: Towards unified image segmentation.NeurIPS,
Reference 51
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:18.613084Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e14b9012-c27e-49f6-9fe8-279d7fb6d50a · outbound
This paper cites Does computer vision matter for action?Science Robotics, 2019.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Does computer vision matter for action?Science Robotics, 2019
Reference 52
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:18.781973Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 18b9b8da-f1dd-4fe5-a2aa-e1ac836b66a5 · outbound
This paper cites Deformable DETR: Deformable Transformers for End-to-End Object Detection.
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving Deformable DETR: Deformable Transformers for End-to-End Object Detection
Reference 53
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:42:18.946960Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
No inbound Pith citation observations are available.