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Action Recognition on THUMOS 14 (test)

84.7mAPR(2+1)D & DSN (M = 1)
32.746.259.773.2Mar 4, 2017Sep 22, 2017Apr 12, 2018Oct 31, 2018May 21, 2019Dec 9, 2019Jun 28, 2020

Evaluation results

MethodLinks
R(2+1)D & DSN (M = 1)Input=RGB+FLOW, Clips=62020.0684.7—
R(2+1)D & DSN (M = 1)Input=RGB, Clips=62020.0683.1—
R(2+1)DInput=RGB+FLOW, Clips=202020.0682.6—
UntrimmedNet (soft)Input=RGB+FLOW, Clips=ALL2020.0682.2—
R(2+1)DInput=RGB, Clips=202020.0681.9—
UntrimmedNet (hard)Input=RGB+FLOW, Clips=ALL2020.0681.2—
TSNInput=RGB+FLOW, Clips=ALL2020.0680.1—
R(2+1)D & DSN (M = 1)Input=FLOW, Clips=62020.0678.4—
R3D-RGB & DSN (M = 6)Input=RGB, Clips=62020.0675.2—
R3D-RGB & TSN (6 seg)Input=RGB, Clips=202020.0673.6—
R(2+1)DInput=FLOW, Clips=202020.0673.5—
Objects+MotionInput=RGB+HOG+HOF+MBH, Clips=ALL2020.0671.6—
Jain et al.Input=HOG+HOF+MBH, Clips=ALL2020.0671—
Two StreamInput=RGB+FLOW, Clips=252020.0666.1—
MotionInput=HOG+HOF+MBH, Clips=ALL2020.0663.1—
ELMInput=HOG+HOF+MBH, Clips=ALL2020.0662.3—
iDT+CNNInput=RGB+iDT, Clips=ALL2020.0662—
RGB+EMVInput=RGB+FLOW2020.0661.5—
CDC2017.0344.4—
Conv & De-convUpsampling method=Separate convolutional and de-convolutional layers2017.0341.7—
MultiLSTMMechanism=Temporal attention2017.0341.3—
LSTMHidden Units=512, Feature Layer=VGG CNN FC72017.0339.3—
CDCTemporal Modeling=Fixed 3D ConvNets2017.0337.4—
C3D + LinearInterpUpsampling method=Linear interpolation, Base Model=C3D2017.0337—
Two-stream CNNInputs=Pixel and Optical Flow2017.0336.2—
Single-frame CNNBackbone=16-layer VGG CNN2017.0334.7—
EMV+RGBSupervision Level=Strong supervision2017.03—61.5
EMV+RGB2017.05—61.5
iDT+FVSupervision Level=Strong supervision2017.03—63.1
iDT+FV2017.05—63.1
object+motion2017.05—71.6
Objects+MotionSupervision Level=Strong supervision2017.03—71.6
TSNNumber of segments=3, Supervision Level=Strong supervision2017.03—78.5
TSNNumber of segments=32017.05—78.8
TSNNumber of segments=72017.05—80.1
Two StreamSupervision Level=Strong supervision2017.03—66.1
Two Stream2017.05—66.1
UntrimmedNetSelection Module=hard, Supervision Level=Weak supervision2017.03—81.2
UntrimmedNetSelection Module=soft, Supervision Level=Weak supervision2017.03—82.2