Papers › DCNAS: Densely Connected Neural Architecture Search for Semantic Image Segmentation
DCNAS: Densely Connected Neural Architecture Search for Semantic Image Segmentation
Xiong Zhang, Hongmin Xu, Hong Mo, Jianchao Tan, Cheng Yang, Lei Wang, Wenqi Ren
Neural Architecture Search (NAS) has shown great potentials in automatically designing scalable network architectures for dense image predictions. However, existing NAS algorithms usually compromise on restricted search space and search on proxy task to meet the achievable computational demands. To allow as wide as possible network architectures and avoid the gap between target and proxy dataset, we propose a Densely Connected NAS (DCNAS) framework, which directly searches the optimal network structures for the multi-scale representations of visual information, over a large-scale target dataset. Specifically, by connecting cells with each other using learnable weights, we introduce a densely connected search space to cover an abundance of mainstream network designs. Moreover, by combining both path-level and channel-level sampling strategies, we design a fusion module to reduce the memory consumption of ample search space. We demonstrate that the architecture obtained from our DCNAS algorithm achieves state-of-the-art performances on public semantic image segmentation benchmarks, including 84.3% on Cityscapes, and 86.9% on PASCAL VOC 2012. We also retain leading performances when evaluating the architecture on the more challenging ADE20K and Pascal Context dataset.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Semantic Segmentation | ADE20K | DCNAS | Validation mIoU | 47.12 | #166 of 235 | Archive leaderboard | report |
| Semantic Segmentation | ADE20K val | DCNAS | mIoU | 47.12 | #67 of 95 | Archive leaderboard | report |
| Semantic Segmentation | Cityscapes test | DCNAS(coarse + Mapillary) | Mean IoU (class) | 83.6% | #13 of 105 | Archive leaderboard | report |
| Semantic Segmentation | PASCAL Context | DCNAS | mIoU | 55.6 | #28 of 66 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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