FoodSeg103 is a new food image dataset containing 7,118 images. Images are annotated with 104 ingredient classes and each image has an average of 6 ingredient labels and pixel-wise masks. It's provided as a large-scale benchmark for food image segmentation.
Major Challenges:
- High intra-variance of the same food ingredient with different cooking methods
- Long-tail distribution
- Complicated contexts
Benchmarks
| Trend | Task | Dataset Variant | Best Model | Paper | Code |
|---|---|---|---|---|---|
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FoodSeg103
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FoodSAM
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Papers
| Paper | Code | Results | Date | Stars |
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