Pith. sign in

Paper Citation Record · LEDGER

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

As of 9 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 2026-08-08T06:32:00.761636+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.

source=pdf_text observed=2026-08-07T00:22:52.604763Z digest=sha256:83b97834e23cb109234be816f889409a5d2a3986d7a4509484253c169efa2cb5

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:52.653218Z digest=sha256:2cbbf633de50b739de5099638e1af0f2417e412cf59a56f88c2b09a6aab85b4f

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:52.768926Z digest=sha256:2b520f4668e095700755f6e402b26a8de126eaee0670217b49ad97ed6a882494

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.

source=pdf_text observed=2026-08-07T00:22:52.868408Z digest=sha256:bf544a7ad56827a85b2ca616b75e0898e0ff678c7c8282a92f8b51c1cf112587

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:52.956061Z digest=sha256:2a9d3486352dfefc425045c139190a506ce3a520b5a0e5560d61a8077a92c2ab

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:53.064780Z digest=sha256:140e41334cf224855216ebfe3a275d184a93a67530b20fe53cf2a312d46614b4

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:53.166453Z digest=sha256:498bdc609ba9e3cdcc10905c92af280c1fd94661d1a35154e7d590b778bd42e9

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:53.298547Z digest=sha256:b91982cd4420e4188cc01bedb7e2b1dd3c394b9a20a6d259c131db7a30983e14

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:53.382994Z digest=sha256:23ee7b214176f67ccd81738a88b4c6ca0551ed09f8cfa635c8c3058040f5e620

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.

source=pdf_text observed=2026-08-07T00:22:53.464307Z digest=sha256:a7b9c03022bbaa525fb80ea33268acac3eeae6a598bafc55b8250e0a96e43922

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:53.527835Z digest=sha256:c915bdc8314ec177ef1551ce8465dfee824b0cb9a3ad7ff02dceeac466d99f7d

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.

source=pdf_text observed=2026-08-07T00:22:53.620449Z digest=sha256:0bf90de56cc184cd6618a7451cd388cd8b7c019cb944ddb26ba4ff5465e5a8d2

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:53.707160Z digest=sha256:85a545d55dbcaa1e1ef14765f5b7fb882e3829b7e7b5bafceeb50e8b8c20f869

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:53.860437Z digest=sha256:f2a11745a69a6a886d3fdab93b8c58b77ff34ed676b48f972bbb64cdc51677f5

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.

source=pdf_text observed=2026-08-07T00:22:53.925483Z digest=sha256:71a393ce2851cfbba9e96b3ee7bec4abbf5b2405e01d4e5b9c55b6fb8145ac24

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:54.000080Z digest=sha256:db0521fdb08394b897556692fa27695abff53e3443c13a814be5e01eca4c61f0

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:54.047920Z digest=sha256:d8057fee149bd6e5eba7457225c54a86981cb59b61eb1eead958b60006d773ff

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:54.117015Z digest=sha256:aa75e46aecdb87af993347712e877a99160577abfeef8f65248f7f7117472731

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:54.188017Z digest=sha256:eca816ed659002af098abd5c7cad4a591477937d4c1b993d04446fe8d7103996

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:54.285067Z digest=sha256:604f1793210a1b07e374792c3b410e09180ec0c9e770480cdc7bf5f61a62badb

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:54.287919Z digest=sha256:ae1c6dcf05060ad29f5405d0c0ae34ee50f6156f4c98db911952c4c850e95d4c

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:54.365441Z digest=sha256:efafa8e4e035a8d48c445b6ba997c9e34cc5600b0f1c61b8243a7150a641a300

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:54.509780Z digest=sha256:b6a89f25b97fbbcbfa300f844a6e3d08a3b22f279f5fec20f57101dc60f3451c

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.

source=pdf_text observed=2026-08-07T00:22:54.592843Z digest=sha256:3536f8f72c601a9333c5480a7eb368c957417ad6afb8c11c8b676efbaad2a439

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:54.681041Z digest=sha256:f290570f98d59ff463df38bcbdffe5b955cc97faf3cb83bfd21da789bab02d88

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.

source=pdf_text observed=2026-08-07T00:22:54.842927Z digest=sha256:ed122cec651c4d822fe1c2ac1d1fdcad664045c9efcce90567f3fefd8c9305cd

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:54.899455Z digest=sha256:fa32eef9e98ee55acc283ec13d30a97f983a7a6121217579c274a4758d3b4f75

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.

source=pdf_text observed=2026-08-07T00:22:55.015238Z digest=sha256:bf6a75374956d41a4c658813e305bf8328e464b7cdf3b04848ca8208d735e338

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.

source=pdf_text observed=2026-08-07T00:22:55.163913Z digest=sha256:fd7d8b42a6b384c87368156e64f57227a79f5a4fcad9a57d9b3993dd10389e16

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:55.291778Z digest=sha256:606fefd6693de98627c2cdf62b4c5a918a9831bc814d03bd3056bc1daca9b763

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:55.411924Z digest=sha256:eff4d66b4dc821b43e3e04cb57b144edbbec89b8c3ba1e56f92ecd43f6ce1d21

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.

source=pdf_text observed=2026-08-07T00:22:55.498293Z digest=sha256:75bc2b76087c41e8a88228c512a440ecb83d7fb51df4de7cd5c91a51fcfc9301

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:55.605680Z digest=sha256:ed1f6a07e9f04377df9496ad6fc2db67bb6ee57378581b41452ba3c8eae5907a

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.

source=pdf_text observed=2026-08-07T00:22:55.733093Z digest=sha256:6c1b85bcffee241ce1071e9f86934366a17a9357d2c3e02741d05bda3fc27d66

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:55.803030Z digest=sha256:0ad475be7319b55d4befad2a910a6ffe8dc9b4fc2f986d0612845d7180816142

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.

source=pdf_text observed=2026-08-07T00:22:55.888999Z digest=sha256:19376eedc2b582f1888c2edfc986b9c392ca610acdc30f2db9b5574b38b0300d

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:55.958866Z digest=sha256:9fcb650fcb4b2fe1d6a10cb104ff5792577513aeda552737955496754b38ad02

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.

source=pdf_text observed=2026-08-07T00:22:56.099146Z digest=sha256:b4f83a019c09d38d1c6e40233b54cb556462f4a14dce95273ef36759b86879e5

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.

source=pdf_text observed=2026-08-07T00:22:56.206226Z digest=sha256:e1bbc795e9a3c333f409d16351fd13f601708c72ee741bd8ff4765741229a8da

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.

source=pdf_text observed=2026-08-07T00:22:56.344291Z digest=sha256:dc97294bdc8b6261f40d2c6606b83bc5f69fe34c89c3a3517712ea1369483f7b

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.

source=pdf_text observed=2026-08-07T00:22:56.472923Z digest=sha256:252464af2dd4dd0e964eafc4b9f5702c08c8c6cb8c3beb9b2a64b60bc77d530f

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.

source=pdf_text observed=2026-08-07T00:22:56.563895Z digest=sha256:501b05a71275c42dcdbb5169d8ffb57e69b32184a327c709f7ae2c2336d20b7e

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:56.694456Z digest=sha256:64ff832a52da8d7dd4060f94a14266db13bd70faac2db0bfc3e111d5e04b0c04

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:56.791227Z digest=sha256:a23cbabbb7f9b216bc74b0d4876cac044bbd10557395d217d9537dc0bcb2159b

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:56.913363Z digest=sha256:7542effadad8563fd52804b929a48b8bc56b1aa3218976e29eb2d59d0cd1161e

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:57.024645Z digest=sha256:f2aa444691b55237caef158c721fd61a47c4f3419858fbe474af3bdd7d0dab7a

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:57.142428Z digest=sha256:909ed6dda33752f7a794416f8037e3afb630fa468092fa2afd79f83e8d224687

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:57.229131Z digest=sha256:a0b6383e0f5465dffc24f308b5b52bd3c89c658767d987c00547cde75782bb7a

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.

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 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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:57.315517Z digest=sha256:58fe5e6f2e8feb225688fa6d891a30f0a7dc9d294e69572b385504ede34147ba

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.

source=pdf_text observed=2026-08-07T00:22:57.450779Z digest=sha256:62232069082f0694fd0cdf966c8f010cb167b38c7931bd4af8a03688e1cb3a34

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:57.588166Z digest=sha256:50eb7df88a3fd9202e1ee84230d78d12cf0bd909ff66e362c47938ad0fabdd78

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:57.715822Z digest=sha256:792b43f4295b396ccff68f5778228f813cdf5f90b9d504f8514fa6ec3aee2c8f

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:57.766572Z digest=sha256:be4010dc1beb70f56022dac7bb73f43d85a01e3d373e1580435c8bb51bc3f8a5

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:57.772013Z digest=sha256:fbf3919021281050890eb99e2cbbba43b26cf0e412f8457fe46fe1276e64f994

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:57.840459Z digest=sha256:177904613ca9405d317e9dd9ef4842d22fd60e7b385e15cd9d6a0c751e49c782

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:57.938891Z digest=sha256:200eef54e8326ffe4fe2bb882b48cb388367e94ce9f0f7546c2749cba1fa2892

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:22:58.067260Z digest=sha256:c55a010d418c191ce84dc2e1bc6595ac11f8f828139afb40897dcec4be10b1ce

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-18T01:55:04.637365Z digest=sha256:5a74dc0f005d764d8f97d655071938bbd23608d410c0dc55cf946845fb0a6b04

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T18:27:39.914591Z digest=sha256:10e69dabe4e9092b49494011f5d3d523bd70047998159a65cb6e32a501d6416b

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.

source=pdf_text observed=2026-08-08T10:24:06.548319Z digest=sha256:875f55a0ae8fc6ea68d80ba0a86347c1d97bb94e89a2811fb30db81a7bf0b4f9