HyperAI초신경
홈뉴스최신 연구 논문튜토리얼데이터셋백과사전SOTALLM 모델GPU 랭킹컨퍼런스
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HyperAI초신경

Temporal Action Localization On Fineaction

평가 지표

mAP
mAP IOU@0.5
mAP IOU@0.75
mAP IOU@0.95

평가 결과

이 벤치마크에서 각 모델의 성능 결과

모델 이름
mAP
mAP IOU@0.5
mAP IOU@0.75
mAP IOU@0.95
Paper TitleRepository
DBG (i3d feature)6.7510.656.432.50Fast Learning of Temporal Action Proposal via Dense Boundary Generator-
ActionMamba(InternVideo2-6B)29.0445.4428.826.79Video Mamba Suite: State Space Model as a Versatile Alternative for Video Understanding
DyFADet (VideoMAE v2-g)23.837.123.75.9DyFADet: Dynamic Feature Aggregation for Temporal Action Detection
RDFA-S6 (InternVideo2-6B)29.646.429.57.6Enhancing Temporal Action Localization: Advanced S6 Modeling with Recurrent Mechanism-
G-TAD (i3d feature)9.0613.748.833.06G-TAD: Sub-Graph Localization for Temporal Action Detection
BMN (i3d feaure)9.2514.448.923.12BMN: Boundary-Matching Network for Temporal Action Proposal Generation
InternVideo17.57---InternVideo: General Video Foundation Models via Generative and Discriminative Learning
InternVideo2-6B27.7---InternVideo2: Scaling Foundation Models for Multimodal Video Understanding
VideoMAE V2-g18.2429.0717.665.07VideoMAE V2: Scaling Video Masked Autoencoders with Dual Masking
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