Papers › Temporal Attentive Alignment for Large-Scale Video Domain Adaptation
Temporal Attentive Alignment for Large-Scale Video Domain Adaptation
Min-Hung Chen, Zsolt Kira, Ghassan AlRegib, Jaekwon Yoo, Ruxin Chen, Jian Zheng
Although various image-based domain adaptation (DA) techniques have been proposed in recent years, domain shift in videos is still not well-explored. Most previous works only evaluate performance on small-scale datasets which are saturated. Therefore, we first propose two large-scale video DA datasets with much larger domain discrepancy: UCF-HMDB_full and Kinetics-Gameplay. Second, we investigate different DA integration methods for videos, and show that simultaneously aligning and learning temporal dynamics achieves effective alignment even without sophisticated DA methods. Finally, we propose Temporal Attentive Adversarial Adaptation Network (TA3N), which explicitly attends to the temporal dynamics using domain discrepancy for more effective domain alignment, achieving state-of-the-art performance on four video DA datasets (e.g. 7.9% accuracy gain over "Source only" from 73.9% to 81.8% on "HMDB --> UCF", and 10.3% gain on "Kinetics --> Gameplay"). The code and data are released at http://github.com/cmhungsteve/TA3N.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Domain Adaptation | HMDB --> UCF (full) | TA3N | Accuracy | 81.79 | #4 of 4 | Archive leaderboard | report |
| Domain Adaptation | UCF --> HMDB (full) | TA3N | Accuracy | 78.33 | #5 of 5 | Archive leaderboard | report |
| Unsupervised Domain Adaptation | EPIC-KITCHENS-100 | TA3N | Average Accuracy | 39.9 | #3 of 5 | Archive leaderboard | report |
| Unsupervised Domain Adaptation | HMDB-UCF | TA3N | Accuracy | 90.54 | #4 of 6 | Archive leaderboard | report |
| Unsupervised Domain Adaptation | Jester (Gesture Recognition) | TA3N | Accuracy | 55.5 | #3 of 5 | Archive leaderboard | report |
| Unsupervised Domain Adaptation | UCF-HMDB | TA3N | Accuracy | 81.38 | #4 of 6 | 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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