paper-with-me

Visual Object Tracking 벤치마크

Visual Object Tracking on TrackingNet

80개 결과 · ⬇ CSV · JSON

Accuracy

53.59 62.17 70.75 79.32 87.9 2015-12 2026-09 STAPLE_CA — 53.59 (2015-12-04) STAPLE_CA — 53.59 (2015-12-04) ECO — 56.13 (2016-11-28) ECO — 56.13 (2016-11-28) ATOM — 70.34 (2018-11-19) ATOM — 70.34 (2018-11-19) SiamRPN++ — 70.0 (2018-12-31) SiamRPN++ — 70.0 (2018-12-31) DiMP-50 — 74.0 (2019-04-15) DiMP-50 — 74.0 (2019-04-15) GFS-DCF — 60.9 (2019-07-30) GFS-DCF — 60.9 (2019-07-30) SiamFC++ — 74.5 (2019-11-14) SiamFC++ — 74.5 (2019-11-14) Siam R-CNN — 81.2 (2019-11-28) Siam R-CNN — 81.2 (2019-11-28) SiamBAN-ACM — 75.3 (2020-12-04) SiamBAN-ACM — 75.3 (2020-12-04) STARK — 82.0 (2021-03-31) STARK — 82.0 (2021-03-31) TREG — 78.5 (2021-04-01) TREG — 78.5 (2021-04-01) SwinTrack-B-384 — 84.0 (2021-12-02) SwinTrack-B-384 — 84.0 (2021-12-02) MixFormer-L — 83.9 (2022-03-21) MixFormer-L — 83.9 (2022-03-21) OSTrack-384 — 83.9 (2022-03-22) OSTrack-384 — 83.9 (2022-03-22) Unicorn — 83.0 (2022-07-14) Unicorn — 83.0 (2022-07-14) AiATrack — 82.7 (2022-07-20) AiATrack — 82.7 (2022-07-20) SLT-TransT — 82.8 (2022-08-11) SLT-TransT — 82.8 (2022-08-11) NeighborTrack-OSTrack — 83.79 (2022-11-12) NeighborTrack-OSTrack — 83.79 (2022-11-12) ARTrack-L — 85.6 (2023-01-01) ARTrack-L — 85.6 (2023-01-01) MixViT-L(ConvMAE) — 86.1 (2023-02-06) MixViT-L(ConvMAE) — 86.1 (2023-02-06) TATrack-L — 85.0 (2023-02-27) TATrack-L — 85.0 (2023-02-27) UNINEXT-H — 85.4 (2023-03-12) UNINEXT-H — 85.4 (2023-03-12) SeqTrack-L384 — 85.5 (2023-04-27) SeqTrack-L384 — 85.5 (2023-04-27) MITS — 83.4 (2023-08-25) MITS — 83.4 (2023-08-25) HIPTrack — 84.5 (2023-11-03) HIPTrack — 84.5 (2023-11-03) ARTrackV2-L — 86.1 (2023-12-28) ARTrackV2-L — 86.1 (2023-12-28) ODTrack-L — 86.1 (2024-01-03) ODTrack-B — 85.1 (2024-01-03) ODTrack-L — 86.1 (2024-01-03) ODTrack-B — 85.1 (2024-01-03) LoRAT-g-378 — 86.0 (2024-03-08) LoRAT-L-378 — 85.6 (2024-03-08) LoRAT-g-378 — 86.0 (2024-03-08) LoRAT-L-378 — 85.6 (2024-03-08) SAMURAI-L — 85.3 (2024-11-18) SAMURAI-L — 85.3 (2024-11-18) MCITrack-L384 — 87.9 (2024-12-15) MCITrack-B224 — 86.3 (2024-12-15) MCITrack-L384 — 87.9 (2024-12-15) MCITrack-B224 — 86.3 (2024-12-15) SPMTrack-G — 87.3 (2025-03-24) SPMTrack-L — 86.9 (2025-03-24) SPMTrack-B — 86.1 (2025-03-24) SPMTrack-G — 87.3 (2025-03-24) SPMTrack-L — 86.9 (2025-03-24) SPMTrack-B — 86.1 (2025-03-24) STAPLE_CA — 53.59 (2015-12-04) ECO — 56.13 (2016-11-28) ATOM — 70.34 (2018-11-19) DiMP-50 — 74.0 (2019-04-15) SiamFC++ — 74.5 (2019-11-14) Siam R-CNN — 81.2 (2019-11-28) STARK — 82.0 (2021-03-31) SwinTrack-B-384 — 84.0 (2021-12-02) ARTrack-L — 85.6 (2023-01-01) MixViT-L(ConvMAE) — 86.1 (2023-02-06) MCITrack-L384 — 87.9 (2024-12-15)
RankModel AccuracyNormalized PrecisionPrecisionSuccess RateAUC PaperCodeYear
1 MCITrack-L384 87.992.189.2 Exploring Enhanced Contextual Information for Video-Level Object Tracking kangben258/MCITrack 2024
2 SPMTrack-G 87.391.488.1 SPMTrack: Spatio-Temporal Parameter-Efficient Fine-Tuning with Mixture of Experts for Scalable Visual Tracking wenruicai/spmtrack 2025
3 SPMTrack-L 86.99187.2 SPMTrack: Spatio-Temporal Parameter-Efficient Fine-Tuning with Mixture of Experts for Scalable Visual Tracking wenruicai/spmtrack 2025
4 MCITrack-B224 86.390.986.1 Exploring Enhanced Contextual Information for Video-Level Object Tracking kangben258/MCITrack 2024
5 ARTrackV2-L 86.190.486.2 ARTrackV2: Prompting Autoregressive Tracker Where to Look and How to Describe miv-xjtu/artrack 2023
5 MixViT-L(ConvMAE) 86.190.386.0 MixFormer: End-to-End Tracking with Iterative Mixed Attention MCG-NJU/MixFormer 2023
5 SPMTrack-B 86.190.285.6 SPMTrack: Spatio-Temporal Parameter-Efficient Fine-Tuning with Mixture of Experts for Scalable Visual Tracking wenruicai/spmtrack 2025
5 ODTrack-L 86.1 ODTrack: Online Dense Temporal Token Learning for Visual Tracking gxnu-zhonglab/odtrack 2024
9 LoRAT-g-378 86.090.286.1 Tracking Meets LoRA: Faster Training, Larger Model, Stronger Performance litinglin/lorat 2024
10 LoRAT-L-378 85.689.785.4 Tracking Meets LoRA: Faster Training, Larger Model, Stronger Performance litinglin/lorat 2024
10 ARTrack-L 85.689.686.0 Autoregressive Visual Tracking miv-xjtu/artrack 2023
12 SeqTrack-L384 85.589.885.8 Unified Sequence-to-Sequence Learning for Single- and Multi-Modal Visual Object Tracking chenxin-dlut/seqtrackv2 2023
13 UNINEXT-H 85.489.086.4 Universal Instance Perception as Object Discovery and Retrieval MasterBin-IIAU/UNINEXT 2023
14 SAMURAI-L 85.3 SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory yangchris11/samurai 2024
15 ODTrack-B 85.1 ODTrack: Online Dense Temporal Token Learning for Visual Tracking gxnu-zhonglab/odtrack 2024
16 TATrack-L 85.089.384.5 Target-Aware Tracking with Long-term Context Attention hekaijie123/TATrack 2023
17 HIPTrack 84.589.183.8 HIPTrack: Visual Tracking with Historical Prompts wenruicai/hiptrack 2023
18 SwinTrack-B-384 8488.283.2 SwinTrack: A Simple and Strong Baseline for Transformer Tracking litinglin/swintrack 2021
19 MixFormer-L 83.988.983.1 MixFormer: End-to-End Tracking with Iterative Mixed Attention MCG-NJU/MixFormer 2022
19 OSTrack-384 83.988.583.2 Joint Feature Learning and Relation Modeling for Tracking: A One-Stream Framework botaoye/ostrack 2022
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