Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T11:49:54.909025Z
Paper Citation Record · LEDGER
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond
As of 12 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2506.01373.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
44 of 44 outbound references displayed
- verified exact1
- verified fuzzy32
- unresolved11
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 0d32e2e0-6f76-45ba-bc4f-5a57b47cac03 · outbound
This paper cites Atkinson and R.M.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Atkinson and R.M
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:50:01.661409Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation c02a1492-a4be-4474-a8c3-c7c68a2ed449 · outbound
This paper cites Evaluating mul- tiple object tracking performance: The clear mot metrics.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Evaluating mul- tiple object tracking performance: The clear mot metrics
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:49:50.971153Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2aa49761-585a-4f19-8cef-3f40b9127c41 · outbound
This paper cites Vision transformer adapters for generalizable multi- task learning, 2023.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Vision transformer adapters for generalizable multi- task learning, 2023
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:50:01.462844Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation fb4d0744-cd5b-4c36-880e-3a4f288c8d55 · outbound
This paper cites Observation-centric sort: Rethink- ing sort for robust multi-object tracking.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Observation-centric sort: Rethink- ing sort for robust multi-object tracking
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:50:01.342101Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 689752c1-0413-4e0b-a958-f0e3750395b2 · outbound
This paper cites Uni- fying short and long-term tracking with graph hierarchies.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Uni- fying short and long-term tracking with graph hierarchies
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:50:01.221164Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 83782fd7-55f6-47a4-a05e-cf55af18a78a · outbound
This paper cites an unresolved cited work.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Unresolved cited work
Reference 6
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:50:00.909906Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 68971a79-667c-41b6-97bb-e25510e6667e · outbound
This paper cites Tracking anything with decoupled video segmentation.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Tracking anything with decoupled video segmentation
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:50:00.679571Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation f5ae6eb9-a6a3-4afc-aa89-3d1aa0083d5d · outbound
This paper cites Putting the object back into video object segmentation.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Putting the object back into video object segmentation
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:50:00.564199Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 304befe3-b69f-418a-851f-6ac32c69ab98 · outbound
This paper cites Soccernet-tracking: Multiple object tracking dataset and benchmark in soccer videos.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Soccernet-tracking: Multiple object tracking dataset and benchmark in soccer videos
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:50:00.507668Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 96c6f261-7fd8-4520-a1b7-a9849e831deb · outbound
This paper cites Sportsmot: A large multi- object tracking dataset in multiple sports scenes.Proceed- ings of the IEEE/CVF International Conference on Com- puter Vision (ICCV), 2023.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Sportsmot: A large multi- object tracking dataset in multiple sports scenes.Proceed- ings of the IEEE/CVF International Conference on Com- puter Vision (ICCV), 2023
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:50:00.360981Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation cb2aa57c-dba7-41d5-af5b-cc3a3cd99946 · outbound
This paper cites Motchal- lenge: A benchmark for single-camera multiple target track- ing.International Journal of Computer Vision, 129:1–37,.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Motchal- lenge: A benchmark for single-camera multiple target track- ing.International Journal of Computer Vision, 129:1–37,
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:50:00.238510Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 3eb31ac7-c6ef-4251-8ac4-722e18058049 · outbound
This paper cites Giaotracker: A compre- hensive framework for mcmot with global information and optimizing strategies in visdrone 2021.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Giaotracker: A compre- hensive framework for mcmot with global information and optimizing strategies in visdrone 2021
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:50:00.124779Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation fdfe2e9c-6223-4bd0-820a-f3312cd5f9b8 · outbound
This paper cites Strongsort: Make deep- sort great again.IEEE Transactions on Multimedia, 2023.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Strongsort: Make deep- sort great again.IEEE Transactions on Multimedia, 2023
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:50:00.007780Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 180913ef-4b9e-467d-9c2d-d1ae52e3278d · outbound
This paper cites MeMOTR: Long-term memory-augmented transformer for multi-object tracking.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond MeMOTR: Long-term memory-augmented transformer for multi-object tracking
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:49:59.885914Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation d89c70d0-8af4-4eda-b8c3-3fbddf9a4e05 · outbound
This paper cites Multiple ob- ject tracking as id prediction, 2024.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Multiple ob- ject tracking as id prediction, 2024
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:49:59.777006Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation e91cf79e-aede-4c8e-9799-f216ad54ab35 · outbound
This paper cites YOLOX: Exceeding YOLO Series in 2021.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond YOLOX: Exceeding YOLO Series in 2021
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:49:52.733414Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 767e2ae1-d854-43a6-85fc-3010b07dd185 · outbound
This paper cites Deep Residual Learning for Image Recognition.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Deep Residual Learning for Image Recognition
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:49:59.655211Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation a244b458-c97a-4936-bf9c-529903b1d16e · outbound
This paper cites Parameter-efficient transfer learning for NLP.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Parameter-efficient transfer learning for NLP
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:49:59.515095Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 107faeab-7833-4d53-be31-2618adb5cbe2 · outbound
This paper cites an unresolved cited work.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Unresolved cited work
Reference 19
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:49:59.312819Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 4f93d724-84a6-4ab9-b3e7-a03564a58d90 · outbound
This paper cites Berg, Wan-Yen Lo, Piotr Doll ´ar, and Ross Girshick.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Berg, Wan-Yen Lo, Piotr Doll ´ar, and Ross Girshick
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:49:59.050677Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 115e07eb-76f8-48a0-9837-c9024263eb80 · outbound
This paper cites an unresolved cited work.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Unresolved cited work
Reference 21
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:49:58.871630Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 1b23639f-350f-492c-ae6c-6556611062f5 · outbound
This paper cites Matching anything by segmenting anything.CVPR, 2024.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Matching anything by segmenting anything.CVPR, 2024
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:49:58.609697Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 609c93d8-04fc-443e-b94c-ec7d42d9e897 · outbound
This paper cites Microsoft COCO: Common Objects in Context.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Microsoft COCO: Common Objects in Context
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:49:53.577116Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7546a4f7-3dce-4637-98a3-82d3e6b8dc35 · outbound
This paper cites Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:49:53.652908Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 31781f77-b731-4ac8-9d47-f21907ca3129 · outbound
This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Swin transformer: Hierarchical vision transformer using shifted windows
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:49:58.431371Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 6a702fe3-36b7-47bc-a93c-7e1e517a6802 · outbound
This paper cites Hota: A higher order metric for evaluating multi-object tracking.International Journal of Computer Vision, pages 1–31, 2020.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Hota: A higher order metric for evaluating multi-object tracking.International Journal of Computer Vision, pages 1–31, 2020
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:49:58.190742Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation d3a5f506-af8f-401e-852e-24d017f6ed69 · outbound
This paper cites Diffmot: A real-time diffusion-based multiple object tracker with non-linear prediction.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Diffmot: A real-time diffusion-based multiple object tracker with non-linear prediction
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:49:57.899789Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation f59e0236-5f13-4d30-9eb6-7879c8a32b14 · outbound
This paper cites Deep OC-SORT: Multi-Pedestrian Tracking by Adaptive Re-Identification.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Deep OC-SORT: Multi-Pedestrian Tracking by Adaptive Re-Identification
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:49:53.949718Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2445fd22-701f-4c3e-8685-09034e1cd6a7 · outbound
This paper cites MOT16: A Benchmark for Multi-Object Tracking.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond MOT16: A Benchmark for Multi-Object Tracking
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:49:53.997148Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fbe3e676-110d-44a6-9d1b-130b1d7c8c84 · outbound
This paper cites Towards generalizable multi-object track- ing.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Towards generalizable multi-object track- ing
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:49:57.581912Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 3930095d-d8be-4591-b002-23afc3a3aa49 · outbound
This paper cites SAM 2: Segment Anything in Images and Videos.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond SAM 2: Segment Anything in Images and Videos
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:49:54.143626Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e2513208-aa69-4576-aefe-bab3f01c4303 · outbound
This paper cites Performance measures and a data set for multi-target, multi-camera tracking.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Performance measures and a data set for multi-target, multi-camera tracking
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:49:54.202989Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c943493e-1d07-45eb-9844-a84faf9f77cb · outbound
This paper cites Orb: an efficient alternative to sift or surf.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Orb: an efficient alternative to sift or surf
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:49:57.284207Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 58bbedb6-f3ea-43cb-b89c-54aafb9ca940 · outbound
This paper cites Dancetrack: Multi-object track- ing in uniform appearance and diverse motion.Proceedings of the IEEE/CVF Conference on Computer Vision and Pat- tern Recognition (CVPR), 2021.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Dancetrack: Multi-object track- ing in uniform appearance and diverse motion.Proceedings of the IEEE/CVF Conference on Computer Vision and Pat- tern Recognition (CVPR), 2021
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:49:57.031880Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 938cd1c6-5ddb-48d4-a85b-fd8cb46b6895 · outbound
This paper cites The Second-place Solution for CVPR 2022 SoccerNet Tracking Challenge.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond The Second-place Solution for CVPR 2022 SoccerNet Tracking Challenge
Reference 35
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T11:49:55.039795Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation ab926bf5-d36c-4468-93f2-300a99ba0806 · outbound
This paper cites Hard to track objects with irregular motions and sim- ilar appearances? make it easier by buffering the matching space.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Hard to track objects with irregular motions and sim- ilar appearances? make it easier by buffering the matching space
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:49:56.795238Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 1f35d5f5-e550-4985-86e5-9bdcb53c321b · outbound
This paper cites Hybrid-sort: Weak cues matter for online multi-object tracking.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Hybrid-sort: Weak cues matter for online multi-object tracking
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:49:56.539178Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 86fb91e6-daa5-4232-96a5-45e72647ad03 · outbound
This paper cites Relationtrack: Relation-aware multiple object tracking with decoupled representation.IEEE Transactions on Multime- dia, 25:2686–2697, 2022.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Relationtrack: Relation-aware multiple object tracking with decoupled representation.IEEE Transactions on Multime- dia, 25:2686–2697, 2022
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:49:56.377883Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation a110a95c-9188-462b-8b85-443f58a19196 · outbound
This paper cites Motr: End-to-end multiple- object tracking with transformer.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Motr: End-to-end multiple- object tracking with transformer
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:49:56.196493Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 4059d19a-c241-45f3-8852-be8c0207ae1e · outbound
This paper cites Fairmot: On the fairness of detection and re-identification in multiple object tracking.International Journal of Computer Vision, 129:3069–3087, 2021.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Fairmot: On the fairness of detection and re-identification in multiple object tracking.International Journal of Computer Vision, 129:3069–3087, 2021
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:49:56.062103Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 5f8cb4bb-56bf-491d-b76b-eaded4e8224a · outbound
This paper cites Bytetrack: Multi-object tracking by associating every detection box.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Bytetrack: Multi-object tracking by associating every detection box
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:49:55.872303Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 8636a7b1-8850-4931-aaf7-7b516e7c9aba · outbound
This paper cites Motrv2: Bootstrapping end-to-end multi-object tracking by pre- trained object detectors.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Motrv2: Bootstrapping end-to-end multi-object tracking by pre- trained object detectors
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:49:55.724000Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 7a0d0927-3b57-4a48-b413-ca30f4cbf775 · outbound
This paper cites Tracking objects as points.Proceedings of the European Conference on Computer Vision (ECCV), 2020.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Tracking objects as points.Proceedings of the European Conference on Computer Vision (ECCV), 2020
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:49:55.494276Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation c578ac7f-9654-459f-9776-5489497eaa2b · outbound
This paper cites Detecting twenty-thousand classes using image-level supervision.
No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond Detecting twenty-thousand classes using image-level supervision
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:49:55.284655Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Pith citing papers
No inbound Pith citation observations are available.