Paper Citation Record · LEDGER

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment

As of 22 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 3 inbound Pith citation observations for arXiv:2506.14271.

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

pith.paper-citation-record.v1
2506.14271 v1

Coverage vector

measured 57 of 57 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:22:58.067260Z

measured 60 of 60 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T10:24:06.548319Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T01:55:37.906296Z

Reference resolution

57 of 57 outbound references displayed

verified exact5
verified fuzzy33
unresolved19
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d7c58b17-c086-48c4-944d-9a60b1c2ccff · outbound

This paper cites Panacea: Panoramic and controllable video generation for autonomous driving.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Panacea: Panoramic and controllable video generation for autonomous driving

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:52.604763Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 569b06f8-0076-4af1-8db1-9ea84fe7b94e · outbound

This paper cites Openmpd: An open multimodal perception dataset for autonomous driving.IEEE Transactions on Vehicular Technology, 71(3):2437–2447, 2022.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Openmpd: An open multimodal perception dataset for autonomous driving.IEEE Transactions on Vehicular Technology, 71(3):2437–2447, 2022

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:23:02.160227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8d5dfdb8-5c68-4b29-b19c-39ed164a7e14 · outbound

This paper cites Semantic cameras for 360-degree environment perception in automated urban driving.IEEE Transactions on Intelligent Transportation Systems, 23(10):17271–17283, 2022.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Semantic cameras for 360-degree environment perception in automated urban driving.IEEE Transactions on Intelligent Transportation Systems, 23(10):17271–17283, 2022

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:23:02.149744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7bac5d7d-4809-4d7b-8402-9adf3c473ab3 · outbound

This paper cites GoodSAM: Bridging Domain and Capacity Gaps via Segment Anything Model for Distortion-aware Panoramic Semantic Segmentation.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment GoodSAM: Bridging Domain and Capacity Gaps via Segment Anything Model for Distortion-aware Panoramic Semantic Segmentation

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:52.868408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4417cf9c-b941-4c78-b1b0-01b3ef51558a · outbound

This paper cites Panovos: Bridging non-panoramic and panoramic views with transformer for video segmentation.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Panovos: Bridging non-panoramic and panoramic views with transformer for video segmentation

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:23:02.139705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b353ac7b-3645-4986-8073-7b5d4f29874e · outbound

This paper cites Detection thresholds for rotation and translation gains in 360 video-based telepresence systems.IEEE transactions on visualization and computer graphics, 24(4):1671–1680, 2018.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Detection thresholds for rotation and translation gains in 360 video-based telepresence systems.IEEE transactions on visualization and computer graphics, 24(4):1671–1680, 2018

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:23:02.128973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3fad7eae-c29e-452f-a593-5f2977d60cd9 · outbound

This paper cites 360vo: Visual odometry using a single 360 camera.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment 360vo: Visual odometry using a single 360 camera

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:23:02.092191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 66256b51-5712-48b1-a080-a02872424e96 · outbound

This paper cites 360+ x: A panoptic multi-modal scene understanding dataset.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment 360+ x: A panoptic multi-modal scene understanding dataset

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:23:02.056086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 06247cfc-c312-405c-be68-35677fcef8f0 · outbound

This paper cites Omniscribe: Authoring immersive audio descriptions for 360 videos.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Omniscribe: Authoring immersive audio descriptions for 360 videos

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:23:02.012052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 91d8456a-ab46-404b-8c9f-5d72b32d0860 · outbound

This paper cites 360VOTS: Visual Object Tracking and Segmentation in Omnidirectional Videos.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment 360VOTS: Visual Object Tracking and Segmentation in Omnidirectional Videos

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:53.464307Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e02fb3ff-d445-498e-b96a-377672ca6181 · outbound

This paper cites Omnidirectional Multi-Object Tracking.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Omnidirectional Multi-Object Tracking

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:22:58.909005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9a237f0d-a4e0-4632-a507-b639494d5029 · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment SAM 2: Segment Anything in Images and Videos

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:53.620449Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e0dfdec1-a005-4198-9593-074dd8e6a814 · outbound

This paper cites 360vot: A new benchmark dataset for omnidirectional visual object tracking.2023 IEEE/CVF International Conference on Computer Vision (ICCV), pages 20509–20519, 2023.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment 360vot: A new benchmark dataset for omnidirectional visual object tracking.2023 IEEE/CVF International Conference on Computer Vision (ICCV), pages 20509–20519, 2023

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:23:01.948176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2a900ec0-3d77-4105-8ea5-05fa41716145 · outbound

This paper cites High quality entity segmentation.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment High quality entity segmentation

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:23:01.819696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0f4e18fc-a3ff-4a62-9813-9c85ad7320c1 · outbound

This paper cites Oneformer: One transformer to rule universal image segmentation.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Oneformer: One transformer to rule universal image segmentation

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:53.925483Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b1946e14-6c4d-41c0-9ac3-753681585161 · outbound

This paper cites an unresolved cited work.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Unresolved cited work

Reference 17

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:23:01.733741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0d054efd-2320-42c3-a9e3-4f07d0fe7990 · outbound

This paper cites Waymo Open Dataset: Panoramic Video Panoptic Segmentation.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Waymo Open Dataset: Panoramic Video Panoptic Segmentation

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:22:58.745329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation aa963aaf-a609-4431-9be7-b3f2bf68c65b · outbound

This paper cites Fine-grained perception in panoramic scenes: A novel task, dataset, and method for object importance ranking.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Fine-grained perception in panoramic scenes: A novel task, dataset, and method for object importance ranking

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:23:01.588095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e668ce63-2e37-4191-a8e3-1d83e3038256 · outbound

This paper cites Lvos: A benchmark for long-term video object segmentation.2023 IEEE/CVF International Conference on Computer Vision (ICCV), pages 13434–13446, 2022.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Lvos: A benchmark for long-term video object segmentation.2023 IEEE/CVF International Conference on Computer Vision (ICCV), pages 13434–13446, 2022

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:23:01.496524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 34f1981c-517b-4249-9162-e96b3cb592f3 · outbound

This paper cites Large-scale video panoptic segmentation in the wild: A benchmark.2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 21001–21011, 2022.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Large-scale video panoptic segmentation in the wild: A benchmark.2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 21001–21011, 2022

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:23:01.484254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9cd0ee89-f47a-49a4-a547-72de4f33dfe0 · outbound

This paper cites Openannotate2: Multi-modal auto-annotating for autonomous driving.IEEE Transactions on Intelligent Vehicles, 2024.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Openannotate2: Multi-modal auto-annotating for autonomous driving.IEEE Transactions on Intelligent Vehicles, 2024

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:23:01.326822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4a389f63-5180-4ed7-a899-2439008c1c83 · outbound

This paper cites Algpt: Multi-agent cooperative framework for open-vocabulary multi-modal auto-annotating in autonomous driving.IEEE Transactions on Intelligent Vehicles, 2024.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Algpt: Multi-agent cooperative framework for open-vocabulary multi-modal auto-annotating in autonomous driving.IEEE Transactions on Intelligent Vehicles, 2024

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:23:01.236961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d52358ba-2c5a-4b29-a5b7-da0582df5375 · outbound

This paper cites Mevis: A large-scale benchmark for video segmentation with motion expressions.2023 IEEE/CVF International Conference on Computer Vision (ICCV), pages 2694–2703, 2023.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Mevis: A large-scale benchmark for video segmentation with motion expressions.2023 IEEE/CVF International Conference on Computer Vision (ICCV), pages 2694–2703, 2023

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:23:01.104090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 93aa1c42-0e3b-4b8a-a83f-dbbcfe28bbee · outbound

This paper cites TrackingNet: A Large-Scale Dataset and Benchmark for Object Tracking in the Wild.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment TrackingNet: A Large-Scale Dataset and Benchmark for Object Tracking in the Wild

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:54.592843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd0f1257-7d32-402a-94d9-db25b96565bf · outbound

This paper cites Lasot: A high-quality benchmark for large-scale single object tracking.2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 5369–5378, 2018.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Lasot: A high-quality benchmark for large-scale single object tracking.2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 5369–5378, 2018

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:23:00.970262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 75722301-3209-4ecb-b65b-ab95655578a4 · outbound

This paper cites TAO: A Large-Scale Benchmark for Tracking Any Object.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment TAO: A Large-Scale Benchmark for Tracking Any Object

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:54.842927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92c21d98-db00-4d5f-8eea-4702228ae477 · outbound

This paper cites 360dvd: Controllable panorama video generation with 360-degree video diffusion model.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment 360dvd: Controllable panorama video generation with 360-degree video diffusion model

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:23:00.923252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 08e313f8-ecab-473b-a5ab-c79c7d7c37e6 · outbound

This paper cites Imagine360: Immersive 360 Video Generation from Perspective Anchor.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Imagine360: Immersive 360 Video Generation from Perspective Anchor

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:55.015238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aad441d2-a39b-4d6e-8477-3e56909f2363 · outbound

This paper cites Segment anything.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Segment anything

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:55.163913Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ee85755-71a1-4937-bd58-add4fa29e15d · outbound

This paper cites E-SAM: Training-Free Segment Every Entity Model.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment E-SAM: Training-Free Segment Every Entity Model

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:22:58.601228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4f7cbf1f-068a-4d3e-99be-c0a02b6dfde5 · outbound

This paper cites Schwing, Alexander Kirillov, and Rohit Girdhar.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Schwing, Alexander Kirillov, and Rohit Girdhar

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:23:00.781062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2389bea0-ac7a-4b09-b953-65a5ae613035 · outbound

This paper cites Schwing, and Alexander Kirillov.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Schwing, and Alexander Kirillov

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:55.498293Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 231ceb61-b745-4761-bb72-5782681e1ca1 · outbound

This paper cites Omg-seg: Is one model good enough for all segmentation? InProceedings of the IEEE/CVF conference on computer vision and pattern recognition, pages 27948–27959, 2024.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Omg-seg: Is one model good enough for all segmentation? InProceedings of the IEEE/CVF conference on computer vision and pattern recognition, pages 27948–27959, 2024

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:23:00.629004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 944be81a-307a-40bc-942f-d7c15af473dd · outbound

This paper cites Microsoft coco: Common objects in context.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Microsoft coco: Common objects in context

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:55.733093Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c7d69616-e5f7-4caf-ba5f-8fbcd986c48c · outbound

This paper cites Semantic understanding of scenes through the ade20k dataset.International Journal of Computer Vision, 127(3):302–321, 2019.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Semantic understanding of scenes through the ade20k dataset.International Journal of Computer Vision, 127(3):302–321, 2019

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:23:00.521545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2e32027b-75ed-4c3b-a538-89ccaaeee341 · outbound

This paper cites The cityscapes dataset for semantic urban scene understanding.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment The cityscapes dataset for semantic urban scene understanding

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:55.888999Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 68212246-3fd3-4cb3-8f5f-b51a55832f38 · outbound

This paper cites EdgeTAM: On-Device Track Anything Model.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment EdgeTAM: On-Device Track Anything Model

Reference 38

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:22:58.507437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8bd98fa8-741e-4cd0-a0fe-e750603b1b46 · outbound

This paper cites Sam2mot: A novel paradigm of multi-object tracking by segmentation.arXiv preprint arXiv:2504.04519, 2025.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Sam2mot: A novel paradigm of multi-object tracking by segmentation.arXiv preprint arXiv:2504.04519, 2025

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:56.099146Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e0014d18-0136-465d-943e-9bb9f9859aca · outbound

This paper cites GPT-4 Technical Report.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment GPT-4 Technical Report

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:56.206226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd1525d8-a887-43ca-b199-8ba7e4e41105 · outbound

This paper cites Personalize Segment Anything Model with One Shot.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Personalize Segment Anything Model with One Shot

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:56.344291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 618ebf3b-5551-4bdf-8149-05bb271a269b · outbound

This paper cites Segment Anything Meets Point Tracking.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Segment Anything Meets Point Tracking

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:56.472923Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bdb8656e-897a-4c91-9ff3-b5eb01142d43 · outbound

This paper cites A benchmark dataset and evaluation methodology for video object segmentation.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment A benchmark dataset and evaluation methodology for video object segmentation

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:56.563895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d73deb9f-aeef-4f28-861c-2caf8ae37b0f · outbound

This paper cites Xmem: Long-term video object segmentation with an atkinson- shiffrin memory model.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Xmem: Long-term video object segmentation with an atkinson- shiffrin memory model

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:23:00.437304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation af555073-3486-42df-89be-14d25a42f5a2 · outbound

This paper cites Associating objects with transformers for video object segmentation.Advances in Neural Information Processing Systems, 34:2491–2502, 2021.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Associating objects with transformers for video object segmentation.Advances in Neural Information Processing Systems, 34:2491–2502, 2021

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:23:00.317167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ee084777-40d0-468a-9e44-e004a9a8bfcc · outbound

This paper cites Siamx: An efficient long-term tracker using cross-level feature correlation and adaptive tracking scheme.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Siamx: An efficient long-term tracker using cross-level feature correlation and adaptive tracking scheme

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:23:00.211436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 63f584fb-8841-4e70-b9c6-4d90d5978a12 · outbound

This paper cites Aiatrack: Attention in attention for transformer visual tracking.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Aiatrack: Attention in attention for transformer visual tracking

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:23:00.047737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0ece874b-6082-4f21-9912-7a81a418d137 · outbound

This paper cites Procontext: Exploring progressive context transformer for tracking.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Procontext: Exploring progressive context transformer for tracking

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:22:59.925280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2068a037-4b76-4a78-9247-7ed121555190 · outbound

This paper cites Backbone is All Your Need: A Simplified Architecture for Visual Object Tracking.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Backbone is All Your Need: A Simplified Architecture for Visual Object Tracking

Reference 49

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:22:58.247446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 087641a3-f792-4db5-8f1f-5cbfe7ec02e1 · outbound

This paper cites Siamx: An efficient long-term tracker using cross-level feature correlation and adaptive tracking scheme.

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:22:59.884957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation afaa8d40-10ce-4a60-8327-f4b0eeb0b72a · outbound

This paper cites YouTube-VOS: A Large-Scale Video Object Segmentation Benchmark.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment YouTube-VOS: A Large-Scale Video Object Segmentation Benchmark

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:57.450779Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8fa477c3-07fe-4129-bda8-4713764a2b1a · outbound

This paper cites Rethinking space-time networks with improved memory coverage for efficient video object segmentation.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Rethinking space-time networks with improved memory coverage for efficient video object segmentation

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:22:59.773121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1ec1e8bb-74a9-4ea4-a72c-4584b259b4f0 · outbound

This paper cites Recurrent dynamic embedding for video object segmentation.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Recurrent dynamic embedding for video object segmentation

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:22:59.682293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation eccbcea3-f1d2-4fa8-8431-748a783b8405 · outbound

This paper cites Xmem++: Production-level video segmentation from few annotated frames.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Xmem++: Production-level video segmentation from few annotated frames

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:22:59.568125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e366422b-cc4f-4d92-b38e-26d96297829d · outbound

This paper cites Trackingnet: A large-scale dataset and benchmark for object tracking in the wild.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Trackingnet: A large-scale dataset and benchmark for object tracking in the wild

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:22:59.425042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 175c3128-b6c2-4c55-b59b-99a4d097eae9 · outbound

This paper cites Pct”: percentage of selected data.“Sel.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment Pct”: percentage of selected data.“Sel

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:22:59.287178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ece2e793-46d8-4fc7-9b2c-dcd0eb67bad1 · outbound

This paper cites an uneven and unreasonable distribution of labels.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment an uneven and unreasonable distribution of labels

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:22:59.249662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 85f5739b-967a-4a42-bfb3-e9378a7853de · outbound

This paper cites penguin" or.

Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment penguin" or

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:22:59.165623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

Observation de96d08c-0454-4990-b45c-25a70f39f877 · inbound

OmniTrack++: Omnidirectional Multi-Object Tracking by Learning Large-FoV Trajectory Feedback cites this paper.

OmniTrack++: Omnidirectional Multi-Object Tracking by Learning Large-FoV Trajectory Feedback Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment

Reference 95

Resolution: verified exact; arxiv_id, observed 2026-05-18T01:55:37.909623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5c84c75e-8362-439f-9619-9cc8152fcb2c · inbound

PanoSAM2: Lightweight Distortion- and Memory-aware Adaptions of SAM2 for 360 Video Object Segmentation cites this paper.

PanoSAM2: Lightweight Distortion- and Memory-aware Adaptions of SAM2 for 360 Video Object Segmentation Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment

Reference 47

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T00:30:55.195963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1aa4f28b-3ea2-41d8-b754-e20c269719dd · inbound

A Multi-Layer System for Ultra-High-Resolution Static 360-Degree Telepresence cites this paper.

A Multi-Layer System for Ultra-High-Resolution Static 360-Degree Telepresence Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-08T10:24:06.548319Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.