paper-with-me

Object Tracking 벤치마크

Object Tracking on FE108

8개 결과 · ⬇ CSV · JSON

Success Rate

26.6 37.08 47.55 58.02 68.5 2018-11 2026-11 ATOM — 46.5 (2018-11-19) DiMP — 57.1 (2019-04-15) KYS — 26.6 (2020-03-24) PrDiMP — 59.0 (2020-03-27) Multi-modal — 63.4 (2021-09-19) HR-MonTrack-Base — 68.5 (2023-07-09) HR-MonTrack-Tiny — 66.3 (2023-07-09) ATOM — 46.5 (2018-11-19) DiMP — 57.1 (2019-04-15) PrDiMP — 59.0 (2020-03-27) Multi-modal — 63.4 (2021-09-19) HR-MonTrack-Base — 68.5 (2023-07-09)
RankModel Success RateAveraged Precision PaperCodeYear
1 HR-MonTrack-Base 68.596.2 Cross-modal Orthogonal High-rank Augmentation for RGB-Event Transformer-trackers zhu-zhiyu/nvs_solver · ZHU-Zhiyu/High-Rank_RGB-Event_Tracker 2023
2 HR-MonTrack-Tiny 66.395.3 Cross-modal Orthogonal High-rank Augmentation for RGB-Event Transformer-trackers zhu-zhiyu/nvs_solver · ZHU-Zhiyu/High-Rank_RGB-Event_Tracker 2023
3 Multi-modal 63.492.4 Object Tracking by Jointly Exploiting Frame and Event Domain Jee-King/ICCV2021_Event_Frame_Tracking · xinli-zn/informative-tracking-benchmark 2021
4 PrDiMP 59.087.7 Probabilistic Regression for Visual Tracking open-mmlab/mmtracking · visionml/pytracking 2020
5 DiMP 57.185.1 Learning Discriminative Model Prediction for Tracking visionml/pytracking · martin-danelljan/ECO 2019
6 MonTrack 54.985.9
7 ATOM 46.571.3 ATOM: Accurate Tracking by Overlap Maximization visionml/pytracking · martin-danelljan/ECO · martin-danelljan/Continuous-ConvOp · +1 2018
8 KYS 26.641.0 Know Your Surroundings: Exploiting Scene Information for Object Tracking visionml/pytracking 2020
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