1 citations · 3 across the 7 of their papers we have counts for
7 papers
Causal Disentanglement for Robust Long-tail Medical Image Generation
Weizhi Nie, Zichun Zhang, Weijie Wang +3
Counterfactual medical image generation effectively addresses data scarcity and enhances the interpretability of medical images. However, due to the complex and diverse pathologica…
BooW-VTON: Boosting In-the-Wild Virtual Try-On via Mask-Free Pseudo Data Training
Xuanpu Zhang, Dan Song, Pengxin Zhan +5
Image-based virtual try-on is an increasingly popular and important task to generate realistic try-on images of the specific person. Recent methods model virtual try-on as image ma…
Better Fit: Accommodate Variations in Clothing Types for Virtual Try-on
Dan Song, Xuanpu Zhang, Jianhao Zeng +4
Image-based virtual try-on aims to transfer target in-shop clothing to a dressed model image, the objectives of which are totally taking off original clothing while preserving the…
CAT-DM: Controllable Accelerated Virtual Try-on with Diffusion Model
Jianhao Zeng, Dan Song, Weizhi Nie +3
Generative Adversarial Networks (GANs) dominate the research field in image-based virtual try-on, but have not resolved problems such as unnatural deformation of garments and the b…
MV-CLIP: Multi-View CLIP for Zero-shot 3D Shape Recognition
Dan Song, Xinwei Fu, Ning Liu +5
Large-scale pre-trained models have demonstrated impressive performance in vision and language tasks within open-world scenarios. Due to the lack of comparable pre-trained models f…
Image-Based Virtual Try-On: A Survey
Dan Song, Xuanpu Zhang, Juan Zhou +4
Image-based virtual try-on aims to synthesize a naturally dressed person image with a clothing image, which revolutionizes online shopping and inspires related topics within image…
Deep Reinforcement Learning Framework for Thoracic Diseases Classification via Prior Knowledge Guidance
Weizhi Nie, Chen Zhang, Dan Song +4
The chest X-ray is often utilized for diagnosing common thoracic diseases. In recent years, many approaches have been proposed to handle the problem of automatic diagnosis based on…