most citedSingle Stage Multi-Pose Virtual Try-On

3 citations · 9 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV20223 cited

Single Stage Multi-Pose Virtual Try-On

Sen He, Yi-Zhe Song, Tao Xiang

Multi-pose virtual try-on (MPVTON) aims to fit a target garment onto a person at a target pose. Compared to traditional virtual try-on (VTON) that fits the garment but keeps the po…

cs.CV20222 cited

FaD-VLP: Fashion Vision-and-Language Pre-training towards Unified Retrieval and Captioning

Suvir Mirchandani, Licheng Yu, Mengjiao Wang +4

Multimodal tasks in the fashion domain have significant potential for e-commerce, but involve challenging vision-and-language learning problems - e.g., retrieving a fashion item gi…

cs.CV2022

Learning to Augment via Implicit Differentiation for Domain Generalization

Tingwei Wang, Da Li, Kaiyang Zhou +2

Machine learning models are intrinsically vulnerable to domain shift between training and testing data, resulting in poor performance in novel domains. Domain generalization (DG) a…

cs.CV20222 cited

Robust Target Training for Multi-Source Domain Adaptation

Zhongying Deng, Da Li, Yi-Zhe Song +1

Given multiple labeled source domains and a single target domain, most existing multi-source domain adaptation (MSDA) models are trained on data from all domains jointly in one ste…

cs.CV2022

Structure-Aware 3D VR Sketch to 3D Shape Retrieval

Ling Luo, Yulia Gryaditskaya, Tao Xiang +1

We study the practical task of fine-grained 3D-VR-sketch-based 3D shape retrieval. This task is of particular interest as 2D sketches were shown to be effective queries for 2D imag…

cs.CV20222 cited

UIGR: Unified Interactive Garment Retrieval

Xiao Han, Sen He, Li Zhang +2

Interactive garment retrieval (IGR) aims to retrieve a target garment image based on a reference garment image along with user feedback on what to change on the reference garment.…