8 papers
InnoText: A Unified Model for Visual Text Generation and Editing
Haowei Liu, Runze He, Jian Lu +10
Diffusion models have recently achieved remarkable success in high-fidelity image synthesis, yet their application to visual text generation and editing remains relatively underexp…
iTryOn: Mastering Interactive Video Virtual Try-On with Spatial-Semantic Guidance
Jun Zheng, Zhengze Xu, Mengting Chen +6
Video Virtual Try-On (VVT) aims to seamlessly replace a garment on a person in a video with a new one. While existing methods have made significant strides in maintaining temporal…
RelaCtrl: Relevance-Guided Efficient Control for Diffusion Transformers
Ke Cao, Jing Wang, Ao Ma +11
The Diffusion Transformer plays a pivotal role in advancing text-to-image and text-to-video generation, owing primarily to its inherent scalability. However, existing controlled di…
FancyVideo: Towards Dynamic and Consistent Video Generation via Cross-frame Textual Guidance
Jiasong Feng, Ao Ma, Jing Wang +2
Synthesizing motion-rich and temporally consistent videos remains a challenge in artificial intelligence, especially when dealing with extended durations. Existing text-to-video (T…
Lay2Story: Extending Diffusion Transformers for Layout-Togglable Story Generation
Ao Ma, Jiasong Feng, Ke Cao +4
Storytelling tasks involving generating consistent subjects have gained significant attention recently. However, existing methods, whether training-free or training-based, continue…
Dynamic Try-On: Taming Video Virtual Try-on with Dynamic Attention Mechanism
Jun Zheng, Jing Wang, Fuwei Zhao +2
Video try-on stands as a promising area for its tremendous real-world potential. Previous research on video try-on has primarily focused on transferring product clothing images to…