1 citations · 1 across the 2 of their papers we have counts for
4 papers
Seeing Like Radiologists: Context- and Gaze-Guided Vision-Language Pretraining for Chest X-rays
Kang Liu, Zhuoqi Ma, Siyu Liang +5
Despite recent advances in medical vision-language pretraining, existing models still struggle to capture the diagnostic workflow: radiographs are typically treated as context-agno…
Noise-Tolerant Hybrid Prototypical Learning with Noisy Web Data
Chao Liang, Linchao Zhu, Zongxin Yang +2
We focus on the challenging problem of learning an unbiased classifier from a large number of potentially relevant but noisily labeled web images given only a few clean labeled ima…
CapHuman: Capture Your Moments in Parallel Universes
Chao Liang, Fan Ma, Linchao Zhu +2
We concentrate on a novel human-centric image synthesis task, that is, given only one reference facial photograph, it is expected to generate specific individual images with divers…
Combating Label Noise With A General Surrogate Model For Sample Selection
Chao Liang, Linchao Zhu, Humphrey Shi +1
Modern deep learning systems are data-hungry. Learning with web data is one of the feasible solutions, but will introduce label noise inevitably, which can hinder the performance o…