Research map / Detection and segmentation / CNN features
Scale-Aware Face Detection
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use scale proposals before detection instead of multi-scale testing | Face detection · FDDB | MFLOPs: 50240 vs 441 + 2704 | Helped |
| Use scale proposals before detection instead of multi-scale testing | Face detection · MALF Whole | MFLOPs: 49807 vs 437 + 8854 | Helped |
| Use scale proposals before detection instead of multi-scale testing | Face detection · AFW | MFLOPs: 49139 vs 432 + 6383 | Helped |
| Use scale proposals before detection instead of multi-scale testing | Face detection · FDDB | Time (ms): 754.75 vs 5.21 + 60.23 | Helped |
| Use scale proposals before detection instead of multi-scale testing | Face detection · MALF Whole | Time (ms): 981.47 vs 11.87 + 190.15 | Helped |
| Use scale proposals before detection instead of multi-scale testing | Face detection · AFW | Time (ms): 427.32 vs 13.17 + 153.66 | Helped |
Closest papers by meaning
- Finding Tiny Faces (CVPR 2017 · similarity 0.88)
- Group Sampling for Scale Invariant Face Detection (CVPR 2019 · similarity 0.87)
- MogFace: Towards a Deeper Appreciation on Face Detection (CVPR 2022 · similarity 0.87)
- Sample and Computation Redistribution for Efficient Face Detection (ICLR 2022 · similarity 0.86)
- Attention-Driven Cropping for Very High Resolution Facial Landmark Detection (CVPR 2020 · similarity 0.85)
- An Analysis of Scale Invariance in Object Detection SNIP (CVPR 2018 · similarity 0.85)
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