Semantic Segmentation on FoodSeg103
Metric: mIoU (higher is better)
Metric: mIoU (higher is better)
| # | Model↕ | mIoU▼ | Extra Data | Paper | Date↕ | Code |
|---|---|---|---|---|---|---|
| 1 | FoodSAM | 46.4 | Yes | FoodSAM: Any Food Segmentation | 2023-08-11 | Code |
| 2 | SeTR-MLA (ViT-16/B) | 45.1 | Yes | Rethinking Semantic Segmentation from a Sequence... | 2020-12-31 | Code |
| 3 | SeTR-Naive (ReLeM-ViT-16/B) | 43.9 | Yes | A Large-Scale Benchmark for Food Image Segmentat... | 2021-05-12 | Code |
| 4 | Swin-Transformer (Swin-Small) | 41.6 | Yes | Swin Transformer: Hierarchical Vision Transforme... | 2021-03-25 | Code |
| 5 | SeTR-Naive (ViT-16/B) | 41.3 | Yes | Rethinking Semantic Segmentation from a Sequence... | 2020-12-31 | Code |
| 6 | CCNet (ReLeM-ResNet-50) | 36.8 | Yes | A Large-Scale Benchmark for Food Image Segmentat... | 2021-05-12 | Code |
| 7 | CCNet (ResNet-50) | 35.5 | Yes | CCNet: Criss-Cross Attention for Semantic Segmen... | 2018-11-28 | Code |