Acne Severity Grading on Face Images via Extraction and Guidance of Prior Knowledge
Acne Vulgaris seriously affects people’s daily life. In this paper, we propose a face acne grading framework which is a new paradigm to solve the image classification problem where the number and type of small objects are the evidence. This framework includes two components: prior knowledge extraction and prior knowledge guided network. The prior knowledge extraction uses an excellent segmentation method to predict the lesion areas as prior knowledge. The prior knowledge guided network fuses the prior knowledge and its corresponding image to grade the severity. The experiment results demonstrate that our framework achieves the state-of-the-art and diagnosis level of dermatologists.
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Ranked #2 on
Acne Severity Grading
on ACNE04
(Accuracy metric)
| Task | Dataset | Model | Metric Name | Metric Value | Global Rank | Benchmark |
|---|---|---|---|---|---|---|
| Acne Severity Grading | ACNE04 | PKGF | Accuracy | 85.27 | # 2 |
