HyperAI超神经

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HyperAI超神经

Visual Object Tracking On Tnl2K

评估指标

AUC

评测结果

各个模型在此基准测试上的表现结果

		Paper Title	Repository
MCITrack-L384	65.3	Exploring Enhanced Contextual Information for Video-Level Object Tracking
MCITrack-B224	62.9	Exploring Enhanced Contextual Information for Video-Level Object Tracking
LoRAT-g-378	62.7	Tracking Meets LoRA: Faster Training, Larger Model, Stronger Performance
LoRAT-L-378	62.3	Tracking Meets LoRA: Faster Training, Larger Model, Stronger Performance
ODTrack-L	61.7	ODTrack: Online Dense Temporal Token Learning for Visual Tracking
ARTrackV2-L	61.6	ARTrackV2: Prompting Autoregressive Tracker Where to Look and How to Describe
ODTrack-B	60.9	ODTrack: Online Dense Temporal Token Learning for Visual Tracking
RTracker-L	60.6	RTracker: Recoverable Tracking via PN Tree Structured Memory
ARTrack-L	60.3	Autoregressive Visual Tracking	-
SeqTrack-L384	57.8	Unified Sequence-to-Sequence Learning for Single- and Multi-Modal Visual Object Tracking
MixFormerV2-B	57.4	-	-
DropTrack	56.9	DropMAE: Learning Representations via Masked Autoencoders with Spatial-Attention Dropout for Temporal Matching Tasks
AdaSwitcher	-	Towards More Flexible and Accurate Object Tracking with Natural Language: Algorithms and Benchmark

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Visual Object Tracking On Tnl2K | SOTA | HyperAI超神经