Research map / Video / Video segmentation and tracking
Learning Temporal Regularity in Video Sequences
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Increase temporal input length T (ablation) | Fully convolutional autoencoder · Video regularity scoring | regularity-score discrimination | Helped |
| Fuse precomputed optical-flow information with grayscale frames (ablation) | Fully convolutional autoencoder · Video regularity scoring | overall performance | No clear effect |
Closest papers by meaning
- Slow and Steady Feature Analysis: Higher Order Temporal Coherence in Video (CVPR 2016 · similarity 0.87)
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- Single-Frame Regularization for Temporally Stable CNNs (CVPR 2019 · similarity 0.86)
- Smooth Regularization for Efficient Video Recognition (NeurIPS 2025 · similarity 0.85)
- Holmes-VAU: Towards Long-term Video Anomaly Understanding at Any Granularity (CVPR 2025 · similarity 0.84)
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