HyperAI초신경

홈 뉴스 최신 연구 논문 튜토리얼 데이터셋 백과사전 SOTA LLM 모델 GPU 랭킹 컨퍼런스

한국어

HyperAI초신경

Object Tracking On Coesot

평가 지표

Precision Rate

Success Rate

평가 결과

이 벤치마크에서 각 모델의 성능 결과

모델 이름	Precision Rate	Success Rate	Paper Title	Repository
AiATrack	67.4	59.0	AiATrack: Attention in Attention for Transformer Visual Tracking	-
KeepTrack	66.1	59.6	Learning Target Candidate Association to Keep Track of What Not to Track	-
HR-CEUTrack-Base	71.9	63.2	Cross-modal Orthogonal High-rank Augmentation for RGB-Event Transformer-trackers	-
SuperDiMP	67.0	60.2	-	-
HR-CEUTrack-Large	73.8	65.0	Cross-modal Orthogonal High-rank Augmentation for RGB-Event Transformer-trackers	-
KYS	66.7	58.6	Know Your Surroundings: Exploiting Scene Information for Object Tracking	-
CEUTrack-Base	70.5	62.0	Revisiting Color-Event based Tracking: A Unified Network, Dataset, and Metric	-
SiamR-CNN	67.5	60.9	Siam R-CNN: Visual Tracking by Re-Detection	-
TransT	67.9	60.5	Transformer Tracking	-
CEUTrack-Large	71.4	62.8	Revisiting Color-Event based Tracking: A Unified Network, Dataset, and Metric	-
OSTrack	66.6	59.0	Joint Feature Learning and Relation Modeling for Tracking: A One-Stream Framework	-
TrDiMP	66.9	60.1	Transformer Meets Tracker: Exploiting Temporal Context for Robust Visual Tracking	-

0 of 12 row(s) selected.

Object Tracking On Coesot | SOTA | HyperAI초신경