Research map / Video / Action recognition
Two-Streams: Dark and Light Networks with Graph Convolution for Action Recognition from Dark Videos (Student Abstract)
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use the two-stream SCI-enhanced R(2+1)D with a temporal GCN instead of DarkLight-R(2+1)D-34 | Proposed Method · ARID V1.0 | Top-1 accuracy: 94.04% -> 95.86% | Helped |
| Use the two-stream SCI-enhanced R(2+1)D with a temporal GCN instead of DarkLight-R(2+1)D-34 | Proposed Method · ARID V1.0 | Top-5 accuracy: 99.87% -> 99.87% | No clear effect |
Closest papers by meaning
- Convolutional Two-Stream Network Fusion for Video Action Recognition (CVPR 2016 · similarity 0.89)
- I Know the Relationships: Zero-Shot Action Recognition via Two-Stream Graph Convolutional Networks and Knowledge Graphs (AAAI 2019 · similarity 0.88)
- Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition (CVPR 2019 · similarity 0.88)
- MARS: Motion-Augmented RGB Stream for Action Recognition (CVPR 2019 · similarity 0.88)
- Spatiotemporal Residual Networks for Video Action Recognition (NeurIPS 2016 · similarity 0.86)
- A Multi-Stream Bi-Directional Recurrent Neural Network for Fine-Grained Action Detection (CVPR 2016 · similarity 0.86)
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