33 citations · 39 across the 7 of their papers we have counts for
7 papers
Consistent Human Image and Video Generation with Spatially Conditioned Diffusion
Mingdeng Cao, Chong Mou, Ziyang Yuan +4
Consistent human-centric image and video synthesis aims to generate images or videos with new poses while preserving appearance consistency with a given reference image, which is c…
OmniDrag: Enabling Motion Control for Omnidirectional Image-to-Video Generation
Weiqi Li, Shijie Zhao, Chong Mou +6
As virtual reality gains popularity, the demand for controllable creation of immersive and dynamic omnidirectional videos (ODVs) is increasing. While previous text-to-ODV generatio…
DiffEditor: Boosting Accuracy and Flexibility on Diffusion-based Image Editing
Chong Mou, Xintao Wang, Jiechong Song +2
Large-scale Text-to-Image (T2I) diffusion models have revolutionized image generation over the last few years. Although owning diverse and high-quality generation capabilities, tra…
Optimization-Inspired Cross-Attention Transformer for Compressive Sensing
Jiechong Song, Chong Mou, Shiqi Wang +2
By integrating certain optimization solvers with deep neural networks, deep unfolding network (DUN) with good interpretability and high performance has attracted growing attention…
Large-capacity and Flexible Video Steganography via Invertible Neural Network
Chong Mou, Youmin Xu, Jiechong Song +3
Video steganography is the art of unobtrusively concealing secret data in a cover video and then recovering the secret data through a decoding protocol at the receiver end. Althoug…
T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Models
Chong Mou, Xintao Wang, Liangbin Xie +5
The incredible generative ability of large-scale text-to-image (T2I) models has demonstrated strong power of learning complex structures and meaningful semantics. However, relying…