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Paper Citation Record · LEDGER

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

As of 13 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 2026-08-13T06:32:02.005865+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:b1299d740b00fa85aabc42d6f5523e1003c1b45d9d7d0a3f9cee46373bf338ee

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:52.653218Z digest=sha256:12ba7df25229a36d335d57e490c1650687f7d5eebad8881d0ceddb9d2c5c6b55

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:52.768926Z digest=sha256:b05120b2ca1eff19bcfe79364ee69645d57e7ee0525482d148fb8989aa956ab2

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:da57c138caccd6ff28dee4eb7b3f7035480d57ab7ff65f66ecdbe70dbafcfa02

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:52.956061Z digest=sha256:aee523a61f0555eb4340aee640fe4b72cb98f6f71f032e5d38f66db3d8b2d14e

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:53.064780Z digest=sha256:ae55ff6a3c13ab5e1e0f6376be994365f1af5d434819d995c676d7cd32e17021

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:53.166453Z digest=sha256:6891ddc71448c3b3d88fd569cfed7a25c87db780b66af66636a6f20368dbd09b

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:53.298547Z digest=sha256:b3680f6949381b4063d7a10bd7752cf0d0291781ff000d74c2ac265adde861d6

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:53.382994Z digest=sha256:99e776d5f78c3ed32344b9daf74f5ccc8a56c07e3d94fd527a51cd58fab0e0d8

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=sha256:0042e953d15caac7252438e1eda9f804f5f416bf005d66d552ce48af83143177

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:53.527835Z digest=sha256:0936586e62a6179e47c3ed8e2666cf4c6a333a097d63adc58afd8fc578a6e61a

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=sha256:42944914a68e2bc94c9889f53221d5548516616e180b7aaba82ad5a34289bf91

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:53.707160Z digest=sha256:c37f3de78aea86030af508f738c6f958d72a0e064c0b4d44b86c3c2deb59dc27

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:53.860437Z digest=sha256:8e1694afe4bf75ca724ec04535e7604dbe97c80f676c18cc4aeaec574b47742c

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:e8d7c1152952404dcf54ec6bb58c10245ee5bbe5e87b2124ce5ee510b6e61669

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:54.000080Z digest=sha256:8501094c001d421245e84873baafd112155322072108418ad6a2aac218039696

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:54.047920Z digest=sha256:f2de9b69934ff29af6d405b21bc9bbaea68408bb343129e771a45949c47b5be4

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:54.117015Z digest=sha256:4ad15b4b6e3f31c14f3424a204d3233e4ed9c2c062578b92dbfb3a0684b4a14e

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:54.188017Z digest=sha256:329eadfa5ae37ca28d08dd8cfac2176a7bc0f8131bc6fc53a5f05bb7c7069e81

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:54.285067Z digest=sha256:e86ba4bc302c968d06d3213bb6b9ff267b012ef7c06dd29f3eed902529a4dd53

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:54.287919Z digest=sha256:35f6996bed8c11a87d4e25d43a9fd09484a3e7c95edb117f9bdaa0c319bf3dfb

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:54.365441Z digest=sha256:92e63ecdebaedb1911dc23455fd2e6fade5048443ee0d6d58a9816d534873827

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:54.509780Z digest=sha256:f46d435caf15ff2a2cd6c011e81927bed60dd018840914c37e22ef08ff260eb0

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:a445db2610d539daa4e3adf4f8e46a8242d6b683551153f57488702e6e40d14c

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:54.681041Z digest=sha256:bdb064369f13a37f81fec78a6e1792ea19d6d86560994b84ff2f76da353516ee

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=sha256:077de581df530682584e1e38cf6a62b0c0baf24e318bed14a4679e3172d0a6ca

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:54.899455Z digest=sha256:0e1ec6f1ba8331cb210703d7be7b30d2d8787d2c43489005f46fb3c9cf32184f

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=sha256:88fed008d21eff465c31cc9b30c0ff6a223680dfa5901959640feda7cfedb0a6

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:dac8c445f40feba947c03725f66f3a0efd39bf4aa7767127d2e571652d2f8fd3

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:55.291778Z digest=sha256:552ebdfd58292bb0a1a9adb7620d093a569406148257df70684d9944d1ba992b

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:55.411924Z digest=sha256:f55713fce735f60f11ad8813392e3385736de5f2ee7ef3e5d505a09a89cf9fa3

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

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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=sha256:6abbd5247e4da949ebc343c243aa13ac3aceb47f68b4788fe0fa17f89a446a4e

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:55.605680Z digest=sha256:583c87bb128e8450f9da98aa2df524c609dd0c46c75be39b0595172865260b81

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

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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=sha256:31e7d95e08024e973a2d365f46e56cb0d6b078c2b3f9b8daf411ca8258111322

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:55.803030Z digest=sha256:75cdb7bd1472cac2ba9572676192ee6751dadaeebeab2d3744a3935613674466

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:b5525bcdecb16b26ed49ec639ad95093298add5ee4ca2c025ddbefdc5aa7df3f

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:55.958866Z digest=sha256:03fbfb2d0c3f5fc4f433ff8f6143b683341b747184b68e44cfc4e1d5d17a37fa

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

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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=sha256:2d85f01e76a555ac9194541909b7d3b49f6a43379aa366d6f3146c92413f5f28

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:a6006e021461352bd1ba859cb7b083849dc8de29e6781d48a985eae95b89efe4

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=sha256:3cd083ca4848f9db3c91f8b2d1dc8eba4b0120332047af7d84ec0a5bb20f8fb1

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=sha256:19e8cc0fe2bf6ce9a1b70d1279e763d7a7fcc225c520ce3583452fc4bd4f2eb7

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:ee3299ad21186d07347eda55f21eb000a8a126cb34c606a7427013f6da9ecba8

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:56.694456Z digest=sha256:45330eb85c1fdee99faa798dd7b5d982a5263883304be41babdb609f49f761e0

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:56.791227Z digest=sha256:eb4de01a8fd8a811b9b5310f2f865fdc2a401936671b5164b4f7c9a7db003ce9

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:56.913363Z digest=sha256:1a62e55d61ee67e46083cab985c1127eed0bfc1099bc1ff4b1595abafacb12a4

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:57.024645Z digest=sha256:f137c9fc3cdd003241b78b3fab8ea4a001712a5c4d045b94905e30630d16be39

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:57.142428Z digest=sha256:0eefba0b8b0d6b9c051172021f536f51e14c64c437fab1975b32dd77515f1ebe

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:57.229131Z digest=sha256:4364fff9edac41775982224e41da32d04e55c8fa406ba07e08f48198ea76d072

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:57.315517Z digest=sha256:41b1dc0af337af32d0b55cc0872fa5b9cd4b3be72318f956c42d30ca3227ad06

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:d71250ddc184da91888500cdb69d40b67cd2b691c553356a374eab9475b9d724

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:57.588166Z digest=sha256:696527af64f78b210a9971ee4fa8b0b0e2a39a329627cfb936e8e87ea48bd1d2

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:57.715822Z digest=sha256:ad3666c364a6131dcf2c0aa39b5a26256b9082f9d8e4b1702e934bae3900b2ec

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:57.766572Z digest=sha256:7000cf0d05ae6791e23f7506bb4438bc2f5189fd89336ad5c4ce0b7bba8b24a9

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:57.772013Z digest=sha256:c971983b82c6c18f81df60351747783d60c47e9101dfaea635e119c3101a9b91

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:57.840459Z digest=sha256:42e5710ea2b190e6e04de4ce240286e15d38a6a03d6ffdcdfc4175b36919f3d4

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:57.938891Z digest=sha256:466673c44da644979e33f4bbb9158acf5b479b5c8221d9a061f345d2882b378d

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:22:58.067260Z digest=sha256:40680d185786e6feadad30430a359e7d1c780a72e2a0a802989f82410ba3244f

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-18T01:55:04.637365Z digest=sha256:26a9fa3bba192502f91b9bd525902c4b9f28da3fc01c4e11d20b9bb905e13883

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-10T18:27:39.914591Z digest=sha256:d28047b513bef7ab0ca3fd2eabf1847fa6843118059cebf8dfd366474108f2e9

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=sha256:898a44e37593d2937db26f800c922332d6561a0443400127954a00bb97956732