| MCITrack-L384 |
- Precision
- 89.2
- Normalized Precision
- 92.1
- Accuracy
- 87.9
|
Exploring Enhanced Contextual Information for Video-Level Object Tracking 2024-12-15 |
코드 1 |
| SPMTrack-G |
- Precision
- 88.1
- Normalized Precision
- 91.4
- Accuracy
- 87.3
|
SPMTrack: Spatio-Temporal Parameter-Efficient Fine-Tuning with Mixture of Experts for Scalable Visual Tracking 2025-03-24 |
코드 1 |
| SPMTrack-L |
- Precision
- 87.2
- Normalized Precision
- 91
- Accuracy
- 86.9
|
SPMTrack: Spatio-Temporal Parameter-Efficient Fine-Tuning with Mixture of Experts for Scalable Visual Tracking 2025-03-24 |
코드 1 |
| MCITrack-B224 |
- Precision
- 86.1
- Normalized Precision
- 90.9
- Accuracy
- 86.3
|
Exploring Enhanced Contextual Information for Video-Level Object Tracking 2024-12-15 |
코드 1 |
| ARTrackV2-L |
- Precision
- 86.2
- Normalized Precision
- 90.4
- Accuracy
- 86.1
|
ARTrackV2: Prompting Autoregressive Tracker Where to Look and How to Describe 2023-12-28 |
코드 1 |
| MixViT-L(ConvMAE) |
- Precision
- 86.0
- Normalized Precision
- 90.3
- Accuracy
- 86.1
|
MixFormer: End-to-End Tracking with Iterative Mixed Attention 2023-02-06 |
코드 1 |
| SPMTrack-B |
- Precision
- 85.6
- Normalized Precision
- 90.2
- Accuracy
- 86.1
|
SPMTrack: Spatio-Temporal Parameter-Efficient Fine-Tuning with Mixture of Experts for Scalable Visual Tracking 2025-03-24 |
코드 1 |
| ODTrack-L |
- Accuracy
- 86.1
|
ODTrack: Online Dense Temporal Token Learning for Visual Tracking 2024-01-03 |
코드 1 |
| LoRAT-g-378 |
- Precision
- 86.1
- Normalized Precision
- 90.2
- Accuracy
- 86.0
|
Tracking Meets LoRA: Faster Training, Larger Model, Stronger Performance 2024-03-08 |
코드 1 |
| LoRAT-L-378 |
- Precision
- 85.4
- Normalized Precision
- 89.7
- Accuracy
- 85.6
|
Tracking Meets LoRA: Faster Training, Larger Model, Stronger Performance 2024-03-08 |
코드 1 |
| ARTrack-L |
- Precision
- 86.0
- Normalized Precision
- 89.6
- Accuracy
- 85.6
|
Autoregressive Visual Tracking 2023-01-01 |
코드 1 |
| SeqTrack-L384 |
- Precision
- 85.8
- Normalized Precision
- 89.8
- Accuracy
- 85.5
|
Unified Sequence-to-Sequence Learning for Single- and Multi-Modal Visual Object Tracking 2023-04-27 |
코드 1 |
| UNINEXT-H |
- Precision
- 86.4
- Normalized Precision
- 89.0
- Accuracy
- 85.4
|
Universal Instance Perception as Object Discovery and Retrieval 2023-03-12 |
코드 1 |
| SAMURAI-L |
- Accuracy
- 85.3
|
SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory 2024-11-18 |
코드 1 |
| ODTrack-B |
- Accuracy
- 85.1
|
ODTrack: Online Dense Temporal Token Learning for Visual Tracking 2024-01-03 |
코드 1 |
| TATrack-L |
- Precision
- 84.5
- Normalized Precision
- 89.3
- Accuracy
- 85.0
|
Target-Aware Tracking with Long-term Context Attention 2023-02-27 |
코드 1 |
| HIPTrack |
- Precision
- 83.8
- Normalized Precision
- 89.1
- Accuracy
- 84.5
|
HIPTrack: Visual Tracking with Historical Prompts 2023-11-03 |
코드 1 |
| SwinTrack-B-384 |
- Precision
- 83.2
- Normalized Precision
- 88.2
- Accuracy
- 84
|
SwinTrack: A Simple and Strong Baseline for Transformer Tracking 2021-12-02 |
코드 1 |
| MixFormer-L |
- Precision
- 83.1
- Normalized Precision
- 88.9
- Accuracy
- 83.9
|
MixFormer: End-to-End Tracking with Iterative Mixed Attention 2022-03-21 |
코드 1 |
| OSTrack-384 |
- Precision
- 83.2
- Normalized Precision
- 88.5
- Accuracy
- 83.9
|
Joint Feature Learning and Relation Modeling for Tracking: A One-Stream Framework 2022-03-22 |
코드 1 |
| NeighborTrack-OSTrack |
- Normalized Precision
- 88.30
- Accuracy
- 83.79
|
NeighborTrack: Improving Single Object Tracking by Bipartite Matching with Neighbor Tracklets 2022-11-12 |
코드 1 |
| MITS |
- Precision
- 84.6
- Normalized Precision
- 88.9
- Accuracy
- 83.4
|
Integrating Boxes and Masks: A Multi-Object Framework for Unified Visual Tracking and Segmentation 2023-08-25 |
코드 1 |
| MixFormerV2-B |
- Precision
- 81.6
- Normalized Precision
- 88.1
- Accuracy
- 83.4
|
연결 없음 논문 날짜 미기재 |
연결 없음 |
| Unicorn |
- Precision
- 82.2
- Normalized Precision
- 86.4
- Accuracy
- 83
|
Towards Grand Unification of Object Tracking 2022-07-14 |
코드 1 |
| SLT-TransT |
- Precision
- 81.4
- Normalized Precision
- 87.5
- Accuracy
- 82.8
|
Towards Sequence-Level Training for Visual Tracking 2022-08-11 |
코드 1 · 코드 2 |
| AiATrack |
- Precision
- 80.4
- Normalized Precision
- 87.8
- Accuracy
- 82.7
|
AiATrack: Attention in Attention for Transformer Visual Tracking 2022-07-20 |
코드 1 |
| STARK |
- Precision
- 79.1
- Normalized Precision
- 86.9
- Accuracy
- 82.0
|
Learning Spatio-Temporal Transformer for Visual Tracking 2021-03-31 |
코드 1 |
| Siam R-CNN |
- Precision
- 80.0
- Normalized Precision
- 85.4
- Accuracy
- 81.2
|
Siam R-CNN: Visual Tracking by Re-Detection 2019-11-28 |
코드 1 |
| TREG |
- Precision
- 75
- Normalized Precision
- 83.8
- Accuracy
- 78.5
|
Target Transformed Regression for Accurate Tracking 2021-04-01 |
코드 1 |
| SiamBAN-ACM |
- Precision
- 71.2
- Normalized Precision
- 81.0
- Accuracy
- 75.3
|
Learning to Fuse Asymmetric Feature Maps in Siamese Trackers 2020-12-04 |
코드 1 |