Papers › CAST: Cross-Attention in Space and Time for Video Action Recognition
CAST: Cross-Attention in Space and Time for Video Action Recognition
DongHo Lee, Jongseo Lee, Jinwoo Choi
Recognizing human actions in videos requires spatial and temporal understanding. Most existing action recognition models lack a balanced spatio-temporal understanding of videos. In this work, we propose a novel two-stream architecture, called Cross-Attention in Space and Time (CAST), that achieves a balanced spatio-temporal understanding of videos using only RGB input. Our proposed bottleneck cross-attention mechanism enables the spatial and temporal expert models to exchange information and make synergistic predictions, leading to improved performance. We validate the proposed method with extensive experiments on public benchmarks with different characteristics: EPIC-KITCHENS-100, Something-Something-V2, and Kinetics-400. Our method consistently shows favorable performance across these datasets, while the performance of existing methods fluctuates depending on the dataset characteristics.
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Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Action Classification | Kinetics-400 | CAST(ViT-B/16) | Acc@1 | 85.3 | #56 of 207 | Archive leaderboard | report |
| Action Recognition | EPIC-KITCHENS-100 | CAST(ViT-B/16) | Action@1 | 49.3 | #10 of 32 | Archive leaderboard | report |
| Action Recognition | EPIC-KITCHENS-100 | CAST(ViT-B/16) | Noun@1 | 60.9 | #10 of 32 | Archive leaderboard | report |
| Action Recognition | EPIC-KITCHENS-100 | CAST(ViT-B/16) | Verb@1 | 72.5 | #10 of 32 | Archive leaderboard | report |
| Action Recognition | Something-Something V2 | CAST(ViT-B/16) | Top-1 Accuracy | 71.6 | #27 of 123 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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