Research map / Detection and segmentation / CNN features
Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Increase filter multiplier from 20 to 48 | Auto-DeepLab · Cityscapes validation | mIOU (%): 79.74 -> 80.33 | Helped |
| Increase training iterations from 500K to 1.5M (ablation) | Auto-DeepLab-S · Cityscapes validation | mIOU (%): 75.20 -> 78.00; 2.8% | Helped |
| Add Scheduled Drop Path (ablation) | Auto-DeepLab-S · Cityscapes validation | mIOU (%): 78.00 -> 79.74; 1.74% | Helped |
| Use coarse annotations | Auto-DeepLab-L · Cityscapes test | mIOU (%): 80.4 -> 82.1 | Helped |
| Use multi-scale inference (ablation) | Auto-DeepLab-L · PASCAL VOC 2012 validation | mIOU (%): 73.76 -> 75.26 | Helped |
| Pretrain on COCO (ablation) | Auto-DeepLab-L · PASCAL VOC 2012 validation | mIOU (%): 73.76 -> 80.75 | Helped |
Closest papers by meaning
- Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells (CVPR 2019 · similarity 0.91)
- Customizable Architecture Search for Semantic Segmentation (CVPR 2019 · similarity 0.91)
- Graph-Guided Architecture Search for Real-Time Semantic Segmentation (CVPR 2020 · similarity 0.91)
- DCNAS: Densely Connected Neural Architecture Search for Semantic Image Segmentation (CVPR 2021 · similarity 0.90)
- Towards Neural Architecture Search through Hierarchical Generative Modeling (ICML 2024 · similarity 0.88)
- einspace: Searching for Neural Architectures from Fundamental Operations (NeurIPS 2024 · similarity 0.87)
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