7 papers
OmniTransfer: All-in-one Framework for Spatio-temporal Video Transfer
Pengze Zhang, Yanze Wu, Mengtian Li +8
Videos convey richer information than images or text, capturing both spatial and temporal dynamics. However, most existing video customization methods rely on reference images or t…
DreamStyle: A Unified Framework for Video Stylization
Mengtian Li, Jinshu Chen, Songtao Zhao +3
Video stylization, an important downstream task of video generation models, has not yet been thoroughly explored. Its input style conditions typically include text, style image, an…
DreamID-V:Bridging the Image-to-Video Gap for High-Fidelity Face Swapping via Diffusion Transformer
Xu Guo, Fulong Ye, Xinghui Li +6
Video Face Swapping (VFS) requires seamlessly injecting a source identity into a target video while meticulously preserving the original pose, expression, lighting, background, and…
DreamO: A Unified Framework for Image Customization
Chong Mou, Yanze Wu, Wenxu Wu +15
Recently, extensive research on image customization (e.g., identity, subject, style, background, etc.) demonstrates strong customization capabilities in large-scale generative mode…
InstructX: Towards Unified Visual Editing with MLLM Guidance
Chong Mou, Qichao Sun, Yanze Wu +5
With recent advances in Multimodal Large Language Models (MLLMs) showing strong visual understanding and reasoning, interest is growing in using them to improve the editing perform…
MUSAR: Exploring Multi-Subject Customization from Single-Subject Dataset via Attention Routing
Zinan Guo, Pengze Zhang, Yanze Wu +3
Current multi-subject customization approaches encounter two critical challenges: the difficulty in acquiring diverse multi-subject training data, and attribute entanglement across…