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Models/EleAtt-GRU (aug.)

EleAtt-GRU (aug.)

Reported on 16 benchmarks across 8 tasks · 1 paper

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Computer Vision6 results

VideoonNTU RGB+D
Accuracy (CS)· 2019-09-03
80.7
best: 94.3 (Hulk(Finetune, ViT-L))
EleAtt-RNN: Adding Attentiveness to Neurons in Recurrent Neural Networks arXiv:1909.01939
VideoonNTU RGB+D
Accuracy (CV)· 2019-09-03
88.4
best: 98.3 (ST-GCN [PYSKL, 2D Skeleton])
EleAtt-RNN: Adding Attentiveness to Neurons in Recurrent Neural Networks arXiv:1909.01939
Temporal Action LocalizationonNTU RGB+D
Accuracy (CS)· 2019-09-03
80.7
best: 94.3 (Hulk(Finetune, ViT-L))
EleAtt-RNN: Adding Attentiveness to Neurons in Recurrent Neural Networks arXiv:1909.01939
Temporal Action LocalizationonNTU RGB+D
Accuracy (CV)· 2019-09-03
88.4
best: 98.3 (ST-GCN [PYSKL, 2D Skeleton])
EleAtt-RNN: Adding Attentiveness to Neurons in Recurrent Neural Networks arXiv:1909.01939
Action LocalizationonNTU RGB+D
Accuracy (CS)· 2019-09-03
80.7
best: 94.3 (Hulk(Finetune, ViT-L))
EleAtt-RNN: Adding Attentiveness to Neurons in Recurrent Neural Networks arXiv:1909.01939
Action LocalizationonNTU RGB+D
Accuracy (CV)· 2019-09-03
88.4
best: 98.3 (ST-GCN [PYSKL, 2D Skeleton])
EleAtt-RNN: Adding Attentiveness to Neurons in Recurrent Neural Networks arXiv:1909.01939

Time Series4 results

Action DetectiononNTU RGB+D
Accuracy (CS)· 2019-09-03
80.7
best: 94.3 (Hulk(Finetune, ViT-L))
EleAtt-RNN: Adding Attentiveness to Neurons in Recurrent Neural Networks arXiv:1909.01939
Action DetectiononNTU RGB+D
Accuracy (CV)· 2019-09-03
88.4
best: 98.3 (ST-GCN [PYSKL, 2D Skeleton])
EleAtt-RNN: Adding Attentiveness to Neurons in Recurrent Neural Networks arXiv:1909.01939
Action RecognitiononNTU RGB+D
Accuracy (CS)· 2019-09-03
80.7
best: 97.4 (DSCNet (RGB + Pose))
EleAtt-RNN: Adding Attentiveness to Neurons in Recurrent Neural Networks arXiv:1909.01939
Action RecognitiononNTU RGB+D
Accuracy (CV)· 2019-09-03
88.4
best: 99.6 (PoseC3D (RGB + Pose))
EleAtt-RNN: Adding Attentiveness to Neurons in Recurrent Neural Networks arXiv:1909.01939

Methodology2 results

Zero-Shot LearningonNTU RGB+D
Accuracy (CS)· 2019-09-03
80.7
best: 94.3 (Hulk(Finetune, ViT-L))
EleAtt-RNN: Adding Attentiveness to Neurons in Recurrent Neural Networks arXiv:1909.01939
Zero-Shot LearningonNTU RGB+D
Accuracy (CV)· 2019-09-03
88.4
best: 98.3 (ST-GCN [PYSKL, 2D Skeleton])
EleAtt-RNN: Adding Attentiveness to Neurons in Recurrent Neural Networks arXiv:1909.01939

Robots2 results

Activity RecognitiononNTU RGB+D
Accuracy (CS)· 2019-09-03
80.7
best: 97.4 (DSCNet (RGB + Pose))
EleAtt-RNN: Adding Attentiveness to Neurons in Recurrent Neural Networks arXiv:1909.01939
Activity RecognitiononNTU RGB+D
Accuracy (CV)· 2019-09-03
88.4
best: 99.6 (PoseC3D (RGB + Pose))
EleAtt-RNN: Adding Attentiveness to Neurons in Recurrent Neural Networks arXiv:1909.01939

Natural Language Processing2 results

3D Action RecognitiononNTU RGB+D
Accuracy (CS)· 2019-09-03
80.7
best: 94.3 (Hulk(Finetune, ViT-L))
EleAtt-RNN: Adding Attentiveness to Neurons in Recurrent Neural Networks arXiv:1909.01939
3D Action RecognitiononNTU RGB+D
Accuracy (CV)· 2019-09-03
88.4
best: 98.3 (ST-GCN [PYSKL, 2D Skeleton])
EleAtt-RNN: Adding Attentiveness to Neurons in Recurrent Neural Networks arXiv:1909.01939