List your company

Action Detection on JHMDB (test)

61.3F@0.5Tube Convolutional Neural Network
32.07639.66347.2554.837Mar 30, 2017Jul 30, 2018Nov 30, 2019Apr 1, 2021Aug 2, 2022Dec 3, 2023Apr 4, 2025

Evaluation results

MethodLinks
Tube Convolutional Neural Networkskip pooling=true2017.0361.3——
Peng et al.2017.0358.5——
SiA-B16 + NWS + AWSTraining Data=AVA-Kinetics without Kinetics-700 labels, NWS=true, AWS=true2025.0457.1——
SiA-B16 + NWSTraining Data=AVA-Kinetics without Kinetics-700 labels, NWS=true, AWS=false2025.0451.5——
Tube Convolutional Neural Networkskip pooling=false2017.0347.9——
Weinzaepfel et al.2017.0345.8——
ViCLIPTraining Data=AVA-Kinetics without Kinetics-700 labels, Evaluation Mode=Open-vocabulary2025.0439.9——
SiA-B16Training Data=AVA-Kinetics without Kinetics-700 labels, NWS=false, AWS=false2025.0439.9——
Gkioxari et al.2017.0336.2——
LanguageBindTraining Data=AVA-Kinetics without Kinetics-700 labels, Evaluation Mode=Open-vocabulary2025.0436.2——
X-CLIPTraining Data=AVA-Kinetics without Kinetics-700 labels, Evaluation Mode=Open-vocabulary2025.0433.2——
Gkioxari et al.2017.03——53.3
Peng et al.2017.03—74.373.1
Tube Convolutional Neural Networkskip pooling=false2017.03—66.958.6
Tube Convolutional Neural Networkskip pooling=true2017.03—78.476.9
Weinzaepfel et al.2017.03—63.160.7