Diffuse to Choose: Enriching Image Conditioned Inpainting in Latent Diffusion Models for Virtual Try-All

24 January 2024

Papers citing "Diffuse to Choose: Enriching Image Conditioned Inpainting in Latent Diffusion Models for Virtual Try-All"

5 / 5 papers shown

Title
CatVTON: Concatenation Is All You Need for Virtual Try-On with Diffusion Models Zheng Chong Xiao Dong Haoxiang Li Shiyue Zhang Wenqing Zhang Xujie Zhang Hanqing Zhao D. Jiang Xiaodan Liang DiffM 48 17 0 21 Jul 2024
DreamPaint: Few-Shot Inpainting of E-Commerce Items for Virtual Try-On without 3D Modeling M. S. Seyfioglu Karim Bouyarmane Suren Kumar A. Tavanaei Ismail B. Tutar DiffM 50 3 0 02 May 2023
DCCF: Deep Comprehensible Color Filter Learning Framework for High-Resolution Image Harmonization Ben Xue Sheng Ran Quan Chen Rongfei Jia Binqiang Zhao Xing Tang 83 59 0 11 Jul 2022
High-Resolution Virtual Try-On with Misalignment and Occlusion-Handled Conditions Sangyun Lee Gyojung Gu S. Park Seunghwan Choi Jaegul Choo DiffM 64 125 0 28 Jun 2022
Zero-Shot Text-to-Image Generation Aditya A. Ramesh Mikhail Pavlov Gabriel Goh Scott Gray Chelsea Voss Alec Radford Mark Chen Ilya Sutskever VLM 253 4,735 0 24 Feb 2021