| SPMTrack-G |
- AUC
- 77.4
- Normalized Precision
- 86.6
- Precision
- 85
|
SPMTrack: Spatio-Temporal Parameter-Efficient Fine-Tuning with Mixture of Experts for Scalable Visual Tracking 2025-03-24 |
코드 1 |
| SPMTrack-L |
- AUC
- 76.8
- Normalized Precision
- 85.9
- Precision
- 84
|
SPMTrack: Spatio-Temporal Parameter-Efficient Fine-Tuning with Mixture of Experts for Scalable Visual Tracking 2025-03-24 |
코드 1 |
| MCITrack-L384 |
- AUC
- 76.6
- Normalized Precision
- 86.1
- Precision
- 85.0
|
Exploring Enhanced Contextual Information for Video-Level Object Tracking 2024-12-15 |
코드 1 |
| LoRAT-g-378 |
- AUC
- 76.2
- Normalized Precision
- 85.3
- Precision
- 83.5
|
Tracking Meets LoRA: Faster Training, Larger Model, Stronger Performance 2024-03-08 |
코드 1 |
| MCITrack-B224 |
- AUC
- 75.3
- Normalized Precision
- 85.6
- Precision
- 83.3
|
Exploring Enhanced Contextual Information for Video-Level Object Tracking 2024-12-15 |
코드 1 |
| LoRAT-L-378 |
- AUC
- 75.1
- Normalized Precision
- 84.1
- Precision
- 82.0
|
Tracking Meets LoRA: Faster Training, Larger Model, Stronger Performance 2024-03-08 |
코드 1 |
| DAM4SAM |
- AUC
- 75.1
|
A Distractor-Aware Memory for Visual Object Tracking with SAM2 2024-11-26 |
코드 1 |
| SPMTrack-B |
- AUC
- 74.9
- Normalized Precision
- 84
- Precision
- 81.7
|
SPMTrack: Spatio-Temporal Parameter-Efficient Fine-Tuning with Mixture of Experts for Scalable Visual Tracking 2025-03-24 |
코드 1 |
| RTracker-L |
- AUC
- 74.7
- Normalized Precision
- 84.5
|
RTracker: Recoverable Tracking via PN Tree Structured Memory 2024-03-28 |
코드 1 |
| SAMURAI-L |
- AUC
- 74.2
- Normalized Precision
- 82.7
- Precision
- 80.2
|
SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory 2024-11-18 |
코드 1 |
| ODTrack-L |
- AUC
- 74.0
|
ODTrack: Online Dense Temporal Token Learning for Visual Tracking 2024-01-03 |
코드 1 |
| ARTrackV2-L |
- AUC
- 73.6
- Normalized Precision
- 82.8
- Precision
- 81.1
|
ARTrackV2: Prompting Autoregressive Tracker Where to Look and How to Describe 2023-12-28 |
코드 1 |
| PiVOT-L |
- AUC
- 73.4
- Normalized Precision
- 84.7
- Precision
- 82.1
|
Improving Visual Object Tracking through Visual Prompting 2024-09-27 |
코드 1 |
| MixViT-L(ConvMAE) |
- AUC
- 73.3
- Normalized Precision
- 82.8
- Precision
- 80.3
|
MixFormer: End-to-End Tracking with Iterative Mixed Attention 2023-02-06 |
코드 1 |
| ODTrack-B |
- AUC
- 73.2
|
ODTrack: Online Dense Temporal Token Learning for Visual Tracking 2024-01-03 |
코드 1 |
| ARTrack-L |
- AUC
- 73.1
- Normalized Precision
- 82.2
- Precision
- 80.3
|
Autoregressive Visual Tracking 2023-01-01 |
코드 1 |
| HIPTrack |
- AUC
- 72.7
- Normalized Precision
- 82.9
- Precision
- 79.5
|
HIPTrack: Visual Tracking with Historical Prompts 2023-11-03 |
코드 1 |
| SeqTrack-L384 |
- AUC
- 72.5
- Normalized Precision
- 81.5
- Precision
- 79.3
|
Unified Sequence-to-Sequence Learning for Single- and Multi-Modal Visual Object Tracking 2023-04-27 |
코드 1 |
| UNINEXT-L |
- AUC
- 72.4
- Normalized Precision
- 80.7
- Precision
- 78.9
|
Universal Instance Perception as Object Discovery and Retrieval 2023-03-12 |
코드 1 |
| NeighborTrack-OSTrack |
- AUC
- 72.2
- Normalized Precision
- 81.8
- Precision
- 78.0
|
NeighborTrack: Improving Single Object Tracking by Bipartite Matching with Neighbor Tracklets 2022-11-12 |
코드 1 |
| UNINEXT-H |
- AUC
- 72.2
- Normalized Precision
- 80.8
- Precision
- 79.4
|
Universal Instance Perception as Object Discovery and Retrieval 2023-03-12 |
코드 1 |
| MITS |
- AUC
- 72.0
- Normalized Precision
- 80.1
- Precision
- 78.5
|
Integrating Boxes and Masks: A Multi-Object Framework for Unified Visual Tracking and Segmentation 2023-08-25 |
코드 1 |
| DropTrack |
- AUC
- 71.8
- Normalized Precision
- 81.8
- Precision
- 78.1
|
DropMAE: Masked Autoencoders with Spatial-Attention Dropout for Tracking Tasks 2023-04-02 |
코드 1 |
| OSTrack-384 |
- AUC
- 71.1
- Normalized Precision
- 81.1
- Precision
- 77.6
|
Joint Feature Learning and Relation Modeling for Tracking: A One-Stream Framework 2022-03-22 |
코드 1 |
| TATrack-L |
- AUC
- 71.1
- Normalized Precision
- 79.1
- Precision
- 76.1
|
Target-Aware Tracking with Long-term Context Attention 2023-02-27 |
코드 1 |
| SwinV2-L 1K-MIM |
- AUC
- 70.7
|
Revealing the Dark Secrets of Masked Image Modeling 2022-05-26 |
코드 1 |
| MixFormerV2-B |
- AUC
- 70.6
- Normalized Precision
- 80.8
- Precision
- 76.2
|
연결 없음 논문 날짜 미기재 |
연결 없음 |
| LoReTrack |
- AUC
- 70.3
- Precision
- 76.2
|
LoReTrack: Efficient and Accurate Low-Resolution Transformer Tracking 2024-05-27 |
코드 1 |
| SwinTrack-B-384 |
- AUC
- 70.2
- Normalized Precision
- 78.4
- Precision
- 75.3
|
SwinTrack: A Simple and Strong Baseline for Transformer Tracking 2021-12-02 |
코드 1 |
| MixFormer-L |
- AUC
- 70.1
- Normalized Precision
- 79.9
- Precision
- 76.3
|
MixFormer: End-to-End Tracking with Iterative Mixed Attention 2022-03-21 |
코드 1 |