A2VIS: Amodal-Aware Approach to Video Instance Segmentation | Paper Citation Record

Observation 02250719-b0c2-4e95-aa5a-788b98ebbb5c · outbound

This paper cites Tarvis: A unified approach for target-based video segmentation, in: Pro- ceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Tarvis: A unified approach for target-based video segmentation, in: Pro- ceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp

Reference 1

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This paper cites an unresolved cited work.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Unresolved cited work

Reference 2

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Observation 6282fdc8-baad-4751-86b0-51a38cadfc15 · outbound

This paper cites Memot: Multi-object tracking with memory, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Memot: Multi-object tracking with memory, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp

Reference 3

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This paper cites an unresolved cited work.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Unresolved cited work

Reference 4

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Observation 9b74d68c-af0d-4a45-bae1-7b63d3a6d07b · outbound

This paper cites Observation-centric sort: Rethinking sort for robust multi-object track- ing, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Observation-centric sort: Rethinking sort for robust multi-object track- ing, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:42:35.146102Z

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Observation b52b7ee6-09a8-49a0-8f6c-ada5205370b7 · outbound

This paper cites Mask2Former for Video Instance Segmentation.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Mask2Former for Video Instance Segmentation

Reference 6

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Observation bc3c520d-7f6e-40c7-9fa9-741952621925 · outbound

This paper cites Masked-attention mask transformer for universal image segmentation, in: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Masked-attention mask transformer for universal image segmentation, in: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp

Reference 7

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Observation 201cfb25-7387-489d-8401-a83a8fd7b31b · outbound

This paper cites Selective attention and the organization of visual information.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Selective attention and the organization of visual information

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:42:35.123368Z

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Observation 87f94d3c-2f16-490e-bc71-1b623f4d24d8 · outbound

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A2VIS: Amodal-Aware Approach to Video Instance Segmentation Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-12T04:42:35.108525Z

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Observation 70f2544b-eb86-4ee6-b26b-f430796a73bc · outbound

This paper cites an unresolved cited work.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Unresolved cited work

Reference 10

Resolution: unresolved; raw_fallback, observed 2026-08-12T04:42:35.093573Z

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Observation ba4c64fb-9483-4fd3-9286-928a866daa19 · outbound

This paper cites Coarse-to-fine amodal segmentation with shape prior, in: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Coarse-to-fine amodal segmentation with shape prior, in: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:42:35.067648Z

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Observation edcb9025-1267-4991-aa38-a17b71cc8f86 · outbound

This paper cites Mask r-cnn, in: Proceedings of the IEEE international conference on computer vision, pp.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Mask r-cnn, in: Proceedings of the IEEE international conference on computer vision, pp

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:42:35.054926Z

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Observation e49bc68b-d83e-4485-8642-6f78afd5b0c8 · outbound

This paper cites Deep residual learning for image recognition, in: Proceedings of the IEEE conference on computer vision and pattern recognition, pp.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Deep residual learning for image recognition, in: Proceedings of the IEEE conference on computer vision and pattern recognition, pp

Reference 13

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Observation 77709a7c-8a57-495d-8305-c86878c0666f · outbound

This paper cites A generalized framework for video instance segmentation, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation A generalized framework for video instance segmentation, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:42:35.023523Z

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Observation 6561fbd1-3956-4620-a01a-e32fac92c8a0 · outbound

This paper cites Vita: Video instance segmentation via object token association.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Vita: Video instance segmentation via object token association

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:42:35.008450Z

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Observation cf501a0c-b0c8-4230-b2be-48c660213ba9 · outbound

This paper cites an unresolved cited work.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Unresolved cited work

Reference 16

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Observation 43134889-f0d3-4011-aad7-4fc9e9b05427 · outbound

This paper cites Minvis: A minimal video instance segmentation framework without video-based training.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Minvis: A minimal video instance segmentation framework without video-based training

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:42:34.979256Z

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Observation aa5600fa-6e37-483f-b2ad-4035abaf3b70 · outbound

This paper cites Video instance seg- mentation using inter-frame communication transformers.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Video instance seg- mentation using inter-frame communication transformers

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:42:34.964804Z

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Observation ac357b47-1b6b-43f9-99b5-5e9cf45d1339 · outbound

This paper cites A theory of visual interpolation in object perception.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation A theory of visual interpolation in object perception

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:42:34.949901Z

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Observation 9fff41b2-4aad-4520-a85f-3268399046fa · outbound

This paper cites Offline-to-online knowl- edge distillation for video instance segmentation, in: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, pp.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Offline-to-online knowl- edge distillation for video instance segmentation, in: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, pp

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:42:34.935800Z

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Observation 90c60dbe-a6f4-49d9-b52f-dc0769299743 · outbound

This paper cites Amodal instance segmentation, in: European Conference on Computer Vision, Springer.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Amodal instance segmentation, in: European Conference on Computer Vision, Springer

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:42:34.922191Z

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Observation ec1365ed-4239-42c6-a2fb-d50c4ace3cb2 · outbound

This paper cites Microsoft coco: Common objects in context, in: European conference on computer vision, Springer.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Microsoft coco: Common objects in context, in: European conference on computer vision, Springer

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:42:34.909110Z

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Observation 382318d1-05f0-426b-b4df-9e6bbc2ef1b0 · outbound

This paper cites Sg-net: Spatial granularity network for one-stage video instance segmentation, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recogni- tion, pp.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Sg-net: Spatial granularity network for one-stage video instance segmentation, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recogni- tion, pp

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:42:34.896364Z

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Observation a36f9ed3-e3ca-4a71-8ea2-0b2bbd7f7c35 · outbound

This paper cites Blade: Box-level supervised amodal segmentation through directed expansion, in: Proceedings of the AAAI Conference on Artificial Intelligence, pp.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Blade: Box-level supervised amodal segmentation through directed expansion, in: Proceedings of the AAAI Conference on Artificial Intelligence, pp

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:42:34.883188Z

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Observation 6b31e1ba-4714-4170-b949-1ceeb55e3c3e · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows, in: Proceedings of the IEEE/CVF international conference on computer vision, pp.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Swin transformer: Hierarchical vision transformer using shifted windows, in: Proceedings of the IEEE/CVF international conference on computer vision, pp

Reference 25

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Observation 7e5e91a2-86b3-4481-aca1-083992f1a49f · outbound

This paper cites Hota: A higher order metric for evaluating multi-object tracking.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Hota: A higher order metric for evaluating multi-object tracking

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:42:34.861145Z

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Observation ca0077ea-ab09-4c88-91d0-a5a85ad83764 · outbound

This paper cites Trackformer: Multi-object tracking with transformers, in: Proceedings 29 of the IEEE/CVF conference on computer vision and pattern recogni- tion, pp.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Trackformer: Multi-object tracking with transformers, in: Proceedings 29 of the IEEE/CVF conference on computer vision and pattern recogni- tion, pp

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:42:34.847853Z

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Observation d2cccd63-a54d-426c-a354-a2ca722d53f4 · outbound

This paper cites Video object segmentation using space-time memory networks, in: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Video object segmentation using space-time memory networks, in: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:42:34.834950Z

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Observation 6c29f5ac-e3dd-4254-9b49-827696399741 · outbound

This paper cites pix2gestalt: Amodal segmentation by synthesiz- ing wholes, in: 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), IEEE Computer Society.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation pix2gestalt: Amodal segmentation by synthesiz- ing wholes, in: 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), IEEE Computer Society

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:42:34.822518Z

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Observation 61f412a5-113b-49a0-92e1-b618fed8e224 · outbound

This paper cites Occluded video instance segmentation: A benchmark.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Occluded video instance segmentation: A benchmark

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:42:34.810742Z

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Observation 2c19913d-9388-4198-989f-78cb4daed242 · outbound

This paper cites Coarse-to- fine video instance segmentation with factorized conditional appearance flows.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Coarse-to- fine video instance segmentation with factorized conditional appearance flows

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:42:34.798651Z

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Observation 6f39d737-190f-4425-9f9d-36c50b80533b · outbound

This paper cites Motiontrack: Learning robust short-term and long-term motions for multi-object tracking, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Motiontrack: Learning robust short-term and long-term motions for multi-object tracking, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:42:34.786431Z

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Observation 946c38d0-2c76-41b6-adb3-96cdc6967190 · outbound

This paper cites Perfor- mance measures and a data set for multi-target, multi-camera tracking, in: European conference on computer vision, Springer.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Perfor- mance measures and a data set for multi-target, multi-camera tracking, in: European conference on computer vision, Springer

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:42:34.773497Z

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Observation 496dee78-d790-49e1-b209-ad22108f6dcf · outbound

This paper cites Dancetrack: Multi-object tracking in uniform appearance and diverse motion, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Dancetrack: Multi-object tracking in uniform appearance and diverse motion, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:42:34.761354Z

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Observation 8be367cc-46fc-417e-a4ec-72631eb3aee6 · outbound

This paper cites Unsupervised Object Learning via Common Fate.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Unsupervised Object Learning via Common Fate

Reference 35

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Observation 241f3bc7-f062-4efc-9eec-6523891c6342 · outbound

This paper cites ShapeFormer: Shape Prior Visible-to-Amodal Transformer-based Amodal Instance Segmentation.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation ShapeFormer: Shape Prior Visible-to-Amodal Transformer-based Amodal Instance Segmentation

Reference 36

Resolution: verified exact; local_arxiv, observed 2026-08-12T04:42:34.584410Z

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Observation ea3f3c5b-e088-4985-b297-f96037895e52 · outbound

This paper cites AISFormer: Amodal Instance Segmentation with Transformer.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation AISFormer: Amodal Instance Segmentation with Transformer

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-12T04:42:34.436022Z

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Observation d9e3c107-c224-4223-8b4e-8a6beaf92c06 · outbound

This paper cites Ov-vis: Open-vocabulary video instance segmentation.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Ov-vis: Open-vocabulary video instance segmentation

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:42:34.747582Z

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Observation c6cf8a95-24ac-4df2-8d6e-bcb0d9bea37b · outbound

This paper cites Seqformer: Se- quential transformer for video instance segmentation, in: European Con- ference on Computer Vision, Springer.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Seqformer: Se- quential transformer for video instance segmentation, in: European Con- ference on Computer Vision, Springer

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:42:34.734183Z

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Observation 899314ca-d4f1-4510-879b-a4edea00f9c3 · outbound

This paper cites In de- fense of online models for video instance segmentation, in: European Conference on Computer Vision, Springer.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation In de- fense of online models for video instance segmentation, in: European Conference on Computer Vision, Springer

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:42:34.721257Z

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Observation af29e1a4-9f47-4436-8416-aaa1126c1e09 · outbound

This paper cites Amodal Segmentation Based on Visible Region Segmentation and Shape Prior.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Amodal Segmentation Based on Visible Region Segmentation and Shape Prior

Reference 41

Resolution: verified exact; local_arxiv, observed 2026-08-12T04:42:34.555263Z

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Observation b3e89677-2577-442b-bc51-c77d281c2a1a · outbound

This paper cites Video instance segmentation, in: Pro- ceedings of the IEEE/CVF International Conference on Computer Vi- sion, pp.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Video instance segmentation, in: Pro- ceedings of the IEEE/CVF International Conference on Computer Vi- sion, pp

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:42:34.708234Z

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Observation 6c7a8bc6-fbad-473a-8e55-931e6ddc4478 · outbound

This paper cites Self-supervised amodal video object segmentation.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Self-supervised amodal video object segmentation

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:42:34.694038Z

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Observation 3b3e1f54-6077-475c-bf77-70a71f68f954 · outbound

This paper cites Motr: End-to-end multiple-object tracking with transformer, in: Euro- pean Conference on Computer Vision, Springer.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Motr: End-to-end multiple-object tracking with transformer, in: Euro- pean Conference on Computer Vision, Springer

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:42:34.680934Z

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Observation 48bbdeca-5207-4b94-b70f-66524cb3d383 · outbound

This paper cites Amodal ground truth and completion in the wild, in: Proceedings of the IEEE/CVF 31 Conference on Computer Vision and Pattern Recognition, pp.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Amodal ground truth and completion in the wild, in: Proceedings of the IEEE/CVF 31 Conference on Computer Vision and Pattern Recognition, pp

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:42:34.668095Z

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Observation c2c124e0-31c0-4aff-9e4b-2d794abfe11b · outbound

This paper cites DVIS: Decoupled Video Instance Segmentation Framework.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation DVIS: Decoupled Video Instance Segmentation Framework

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-12T04:42:34.471447Z

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Observation 96c7501d-659c-4a37-8812-844f635c5301 · outbound

This paper cites Bytetrack: Multi-object tracking by associat- ing every detection box, in: European Conference on Computer Vision, Springer.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Bytetrack: Multi-object tracking by associat- ing every detection box, in: European Conference on Computer Vision, Springer

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:42:34.655587Z

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Observation 4d0502c3-7402-4d06-b133-cbf9cd1c8ec3 · outbound

This paper cites Fairmot: On the fairness of detection and re-identification in multiple object tracking.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Fairmot: On the fairness of detection and re-identification in multiple object tracking

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:42:34.642755Z

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Observation 4243bee1-1125-4d31-a920-73ad513c6358 · outbound

This paper cites Motrv2: Bootstrapping end-to- end multi-object tracking by pretrained object detectors, in: Proceed- ings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Motrv2: Bootstrapping end-to- end multi-object tracking by pretrained object detectors, in: Proceed- ings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:42:34.627472Z

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Observation 1afbdc35-72bb-49b2-ae75-feb87855366b · outbound

This paper cites Deformable DETR: Deformable Transformers for End-to-End Object Detection.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Deformable DETR: Deformable Transformers for End-to-End Object Detection

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-12T04:42:34.488335Z

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Observation 96b61c04-92ab-4614-8758-18ba7008c178 · outbound

This paper cites an unresolved cited work.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Unresolved cited work

Reference 2019

Resolution: unresolved; raw_fallback, observed 2026-08-12T04:42:35.079844Z

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Observation 0b1f5a2d-6b89-4965-a2be-6fb61268462f · outbound

This paper cites an unresolved cited work.

A2VIS: Amodal-Aware Approach to Video Instance Segmentation Unresolved cited work

Reference 2020

Resolution: unresolved; raw_fallback, observed 2026-08-12T04:42:35.159910Z

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