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Action Classification
Action Classification On Toyota Smarthome
Action Classification On Toyota Smarthome
Metrics
CS
CV1
CV2
Results
Performance results of various models on this benchmark
Columns
Model Name
CS
CV1
CV2
Paper Title
Repository
VPN (RGB + Pose)
60.8
43.8
53.5
VPN: Learning Video-Pose Embedding for Activities of Daily Living
MMNet
70.1
-
-
MMNet: A Model-Based Multimodal Network for Human Action Recognition in RGB-D Videos
Dense Trajectories
41.9
20.9
23.7
Improved Dense Trajectory with Cross Streams
-
Separable STA (RGB + Pose)
54.2
35.2
50.3
Toyota Smarthome: Real-World Activities of Daily Living
-
π-ViT
72.9
55.2
64.8
Just Add $π$! Pose Induced Video Transformers for Understanding Activities of Daily Living
I3D
53.4
34.9
45.1
Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset
NPL
-
39.6
54.6
Recognizing Actions in Videos from Unseen Viewpoints
-
Trans4SOAR (Pose)
-
-
-
Delving Deep into One-Shot Skeleton-based Action Recognition with Diverse Occlusions
UNIK
64.3
36.1
65.0
UNIK: A Unified Framework for Real-world Skeleton-based Action Recognition
AIRStreams
62.11
-
-
Adaptive Intermediate Representations for Video Understanding
-
I3D + Non Local
53.6
34.3
43.9
Non-local Neural Networks
AssembleNet++
63.6
-
-
AssembleNet++: Assembling Modality Representations via Attention Connections
0 of 12 row(s) selected.
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