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Models/SA-DVAE + augmented text

SA-DVAE + augmented text

Reported on 28 benchmarks across 7 tasks · 1 paper · 28 SOTA

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

Computer Vision12 results

VideoonNTU RGB+D 120
Random Split Accuracy· 2024-07-18
57.16
best: 71.38 (PGFA)
SOTA
SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders arXiv:2407.13460
VideoonNTU RGB+D
Random Split Accuracy· 2024-07-18
87.61
best: 93.17 (PGFA)
SOTA
SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders arXiv:2407.13460
VideoonNTU RGB+D
Random Split Harmonic Mean· 2024-07-18
75.51
SOTA
SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders arXiv:2407.13460
VideoonNTU RGB+D 120
Random Split Harmonic Mean· 2024-07-18
50.72
SOTA
SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders arXiv:2407.13460
Temporal Action LocalizationonNTU RGB+D 120
Random Split Accuracy· 2024-07-18
57.16
best: 71.38 (PGFA)
SOTA
SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders arXiv:2407.13460
Temporal Action LocalizationonNTU RGB+D
Random Split Accuracy· 2024-07-18
87.61
best: 93.17 (PGFA)
SOTA
SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders arXiv:2407.13460
Temporal Action LocalizationonNTU RGB+D
Random Split Harmonic Mean· 2024-07-18
75.51
SOTA
SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders arXiv:2407.13460
Temporal Action LocalizationonNTU RGB+D 120
Random Split Harmonic Mean· 2024-07-18
50.72
SOTA
SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders arXiv:2407.13460
Action LocalizationonNTU RGB+D 120
Random Split Accuracy· 2024-07-18
57.16
best: 71.38 (PGFA)
SOTA
SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders arXiv:2407.13460
Action LocalizationonNTU RGB+D
Random Split Accuracy· 2024-07-18
87.61
best: 93.17 (PGFA)
SOTA
SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders arXiv:2407.13460
Action LocalizationonNTU RGB+D
Random Split Harmonic Mean· 2024-07-18
75.51
SOTA
SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders arXiv:2407.13460
Action LocalizationonNTU RGB+D 120
Random Split Harmonic Mean· 2024-07-18
50.72
SOTA
SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders arXiv:2407.13460

Methodology4 results

Zero-Shot LearningonNTU RGB+D 120
Random Split Accuracy· 2024-07-18
57.16
best: 71.38 (PGFA)
SOTA
SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders arXiv:2407.13460
Zero-Shot LearningonNTU RGB+D
Random Split Accuracy· 2024-07-18
87.61
best: 93.17 (PGFA)
SOTA
SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders arXiv:2407.13460
Zero-Shot LearningonNTU RGB+D
Random Split Harmonic Mean· 2024-07-18
75.51
SOTA
SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders arXiv:2407.13460
Zero-Shot LearningonNTU RGB+D 120
Random Split Harmonic Mean· 2024-07-18
50.72
SOTA
SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders arXiv:2407.13460

Robots4 results

Activity RecognitiononNTU RGB+D 120
Random Split Accuracy· 2024-07-18
57.16
best: 71.38 (PGFA)
SOTA
SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders arXiv:2407.13460
Activity RecognitiononNTU RGB+D
Random Split Accuracy· 2024-07-18
87.61
best: 93.17 (PGFA)
SOTA
SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders arXiv:2407.13460
Activity RecognitiononNTU RGB+D
Random Split Harmonic Mean· 2024-07-18
75.51
SOTA
SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders arXiv:2407.13460
Activity RecognitiononNTU RGB+D 120
Random Split Harmonic Mean· 2024-07-18
50.72
SOTA
SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders arXiv:2407.13460

Natural Language Processing4 results

3D Action RecognitiononNTU RGB+D 120
Random Split Accuracy· 2024-07-18
57.16
best: 71.38 (PGFA)
SOTA
SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders arXiv:2407.13460
3D Action RecognitiononNTU RGB+D
Random Split Accuracy· 2024-07-18
87.61
best: 93.17 (PGFA)
SOTA
SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders arXiv:2407.13460
3D Action RecognitiononNTU RGB+D
Random Split Harmonic Mean· 2024-07-18
75.51
SOTA
SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders arXiv:2407.13460
3D Action RecognitiononNTU RGB+D 120
Random Split Harmonic Mean· 2024-07-18
50.72
SOTA
SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders arXiv:2407.13460

Time Series4 results

Action RecognitiononNTU RGB+D 120
Random Split Accuracy· 2024-07-18
57.16
best: 71.38 (PGFA)
SOTA
SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders arXiv:2407.13460
Action RecognitiononNTU RGB+D
Random Split Accuracy· 2024-07-18
87.61
best: 93.17 (PGFA)
SOTA
SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders arXiv:2407.13460
Action RecognitiononNTU RGB+D
Random Split Harmonic Mean· 2024-07-18
75.51
SOTA
SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders arXiv:2407.13460
Action RecognitiononNTU RGB+D 120
Random Split Harmonic Mean· 2024-07-18
50.72
SOTA
SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders arXiv:2407.13460