paper-with-me

Visual Object Tracking 벤치마크

Visual Object Tracking on NeedForSpeed

20개 결과 · ⬇ CSV · JSON

AUC

0.65 0.6605 0.671 0.6815 0.692 2020-05 2026-11 DiMP-NCE+ — 0.65 (2020-05-04) DiMP-NCE+ — 0.65 (2020-05-04) AiATrack — 0.679 (2022-07-20) AiATrack — 0.679 (2022-07-20) SeqTrack-L384 — 0.662 (2023-04-27) SeqTrack-L384 — 0.662 (2023-04-27) HIPTrack — 0.681 (2023-11-03) HIPTrack — 0.681 (2023-11-03) ARTrackV2-L — 0.684 (2023-12-28) ARTrackV2-L — 0.684 (2023-12-28) LoRAT-g-378 — 0.681 (2024-03-08) LoRAT-L-378 — 0.667 (2024-03-08) LoRAT-g-378 — 0.681 (2024-03-08) LoRAT-L-378 — 0.667 (2024-03-08) PiVOT-L — 0.682 (2024-09-27) PiVOT-L — 0.682 (2024-09-27) SAMURAI-L — 0.692 (2024-11-18) SAMURAI-L — 0.692 (2024-11-18) SPMTrack-B — 0.674 (2025-03-24) SPMTrack-B — 0.674 (2025-03-24) DiMP-NCE+ — 0.65 (2020-05-04) AiATrack — 0.679 (2022-07-20) HIPTrack — 0.681 (2023-11-03) ARTrackV2-L — 0.684 (2023-12-28) SAMURAI-L — 0.692 (2024-11-18)
RankModel AUC PaperCodeYear
1 SAMURAI-L 0.692 SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory yangchris11/samurai 2024
2 ARTrackV2-L 0.684 ARTrackV2: Prompting Autoregressive Tracker Where to Look and How to Describe miv-xjtu/artrack 2023
3 PiVOT-L 0.682 Improving Visual Object Tracking through Visual Prompting chenshihfang/GOT 2024
4 HIPTrack 0.681 HIPTrack: Visual Tracking with Historical Prompts wenruicai/hiptrack 2023
4 LoRAT-g-378 0.681 Tracking Meets LoRA: Faster Training, Larger Model, Stronger Performance litinglin/lorat 2024
6 AiATrack 0.679 AiATrack: Attention in Attention for Transformer Visual Tracking Little-Podi/AiATrack 2022
7 SPMTrack-B 0.674 SPMTrack: Spatio-Temporal Parameter-Efficient Fine-Tuning with Mixture of Experts for Scalable Visual Tracking wenruicai/spmtrack 2025
8 LoRAT-L-378 0.667 Tracking Meets LoRA: Faster Training, Larger Model, Stronger Performance litinglin/lorat 2024
9 SeqTrack-L384 0.662 Unified Sequence-to-Sequence Learning for Single- and Multi-Modal Visual Object Tracking chenxin-dlut/seqtrackv2 2023
10 DiMP-NCE+ 0.65 How to Train Your Energy-Based Model for Regression fregu856/ebms_regression · soran-ghaderi/torchebm 2020
11 SAMURAI-L 0.692 SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory yangchris11/samurai 2024
12 ARTrackV2-L 0.684 ARTrackV2: Prompting Autoregressive Tracker Where to Look and How to Describe miv-xjtu/artrack 2023
13 PiVOT-L 0.682 Improving Visual Object Tracking through Visual Prompting chenshihfang/GOT 2024
14 HIPTrack 0.681 HIPTrack: Visual Tracking with Historical Prompts wenruicai/hiptrack 2023
14 LoRAT-g-378 0.681 Tracking Meets LoRA: Faster Training, Larger Model, Stronger Performance litinglin/lorat 2024
16 AiATrack 0.679 AiATrack: Attention in Attention for Transformer Visual Tracking Little-Podi/AiATrack 2022
17 SPMTrack-B 0.674 SPMTrack: Spatio-Temporal Parameter-Efficient Fine-Tuning with Mixture of Experts for Scalable Visual Tracking wenruicai/spmtrack 2025
18 LoRAT-L-378 0.667 Tracking Meets LoRA: Faster Training, Larger Model, Stronger Performance litinglin/lorat 2024
19 SeqTrack-L384 0.662 Unified Sequence-to-Sequence Learning for Single- and Multi-Modal Visual Object Tracking chenxin-dlut/seqtrackv2 2023
20 DiMP-NCE+ 0.65 How to Train Your Energy-Based Model for Regression fregu856/ebms_regression · soran-ghaderi/torchebm 2020
1–20 / 20 페이지당 10 20 50 100