95 citations · 194 across the 18 of their papers we have counts for
5 papers · 1 filter
Neural Video Fields Editing
Shuzhou Yang, Chong Mou, Jiwen Yu +3
Diffusion models have revolutionized text-driven video editing. However, applying these methods to real-world editing encounters two significant challenges: (1) the rapid increase…
DragonDiffusion: Enabling Drag-style Manipulation on Diffusion Models
Chong Mou, Xintao Wang, Jiechong Song +2
Despite the ability of existing large-scale text-to-image (T2I) models to generate high-quality images from detailed textual descriptions, they often lack the ability to precisely…
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…