Research map / Detection and segmentation / CNN features
Semantic Channels for Fast Pedestrian Detection
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add raw and CRF semantic channels to the multiresolution channels (ablation) | Semantic Channels pedestrian detector · Caltech-USA reasonable | log-average miss rate | Helped |
| Use 7 multiresolution scales (ablation) | Semantic Channels pedestrian detector · Caltech-USA reasonable | log-average miss rate | Helped |
| Use denser feature-sampling grids (ablation) | Semantic Channels pedestrian detector · Caltech-USA reasonable | log-average miss rate | No clear effect |
| Add a fifth bootstrapping round with 4096 weak learners (ablation) | Semantic Channels pedestrian detector · Caltech-USA reasonable | log-average miss rate | Hurt |
| Use deeper decision trees (ablation) | Semantic Channels pedestrian detector · Caltech-USA reasonable | log-average miss rate | Hurt |
Closest papers by meaning
- High-Level Semantic Feature Detection: A New Perspective for Pedestrian Detection (CVPR 2019 · similarity 0.88)
- VLPD: Context-Aware Pedestrian Detection via Vision-Language Semantic Self-Supervision (CVPR 2023 · similarity 0.86)
- Localized Semantic Feature Mixers for Efficient Pedestrian Detection in Autonomous Driving (CVPR 2023 · similarity 0.86)
- Occluded Pedestrian Detection Through Guided Attention in CNNs (CVPR 2018 · similarity 0.85)
- Fast Boosting Based Detection Using Scale Invariant Multimodal Multiresolution Filtered Features (CVPR 2017 · similarity 0.84)
- How Far Are We From Solving Pedestrian Detection? (CVPR 2016 · similarity 0.84)
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