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홈뉴스연구 논문튜토리얼데이터셋백과사전SOTALLM 모델GPU 랭킹컨퍼런스
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Visual Object Tracking On Tnl2K

평가 지표

AUC

평가 결과

이 벤치마크에서 각 모델의 성능 결과

모델 이름
AUC
Paper TitleRepository
MCITrack-B22462.9Exploring Enhanced Contextual Information for Video-Level Object Tracking
RTracker-L60.6RTracker: Recoverable Tracking via PN Tree Structured Memory
MixFormerV2-B57.4--
LoRAT-g-37862.7Tracking Meets LoRA: Faster Training, Larger Model, Stronger Performance
MCITrack-L38465.3Exploring Enhanced Contextual Information for Video-Level Object Tracking
ARTrackV2-L61.6ARTrackV2: Prompting Autoregressive Tracker Where to Look and How to Describe
SeqTrack-L38457.8Unified Sequence-to-Sequence Learning for Single- and Multi-Modal Visual Object Tracking
AdaSwitcher-Towards More Flexible and Accurate Object Tracking with Natural Language: Algorithms and Benchmark
ODTrack-B60.9ODTrack: Online Dense Temporal Token Learning for Visual Tracking
ARTrack-L60.3Autoregressive Visual Tracking-
ODTrack-L61.7ODTrack: Online Dense Temporal Token Learning for Visual Tracking
DropTrack56.9DropMAE: Learning Representations via Masked Autoencoders with Spatial-Attention Dropout for Temporal Matching Tasks
LoRAT-L-37862.3Tracking Meets LoRA: Faster Training, Larger Model, Stronger Performance
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