Synthetic Image Oversampling for Rare-Class Representation Learning in Deep Facial Phenotyping
Paper recorded by Signals 4 on 2026-10-16 in cs.CV. Abstract reproduced from arXiv; link to the original below.
Published 2026-10-16 on arXiv · recorded by Signals 4 on 2026-10-19
Category: cs.CV · 计算机视觉 · first seen 2026-10-19
Abstract
Recent deep facial phenotyping methods can support the recognition of genetic syndromes, but patient images are often scarce and unevenly distributed across disorders. Synthetic facial images offer a way to supplement the training data without collecting additional patient photographs. Their usefulness, however, depends on whether they improve recognition of real patients: generated images may int
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Cite this page: Synthetic Image Oversampling for Rare-Class Representation Learning in Deep Facial Phenotyping: the #239 most recent of 756 cs.CV papers we have recorded (as of 2026-10-16). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/synthetic-image-oversampling-for-rare-class-representation-learning-in-deep-faci.html
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