1 citations · 2 across the 11 of their papers we have counts for
11 papers
DreamID-Omni: Unified Framework for Controllable Human-Centric Audio-Video Generation
Xu Guo, Fulong Ye, Qichao Sun +7
Recent advancements in foundation models have revolutionized joint audio-video generation. However, existing approaches typically treat human-centric tasks including reference-base…
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…
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…
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…
OmniInsert: Mask-Free Video Insertion of Any Reference via Diffusion Transformer Models
Jinshu Chen, Xinghui Li, Xu Bai +8
Recent advances in video insertion based on diffusion models are impressive. However, existing methods rely on complex control signals but struggle with subject consistency, limiti…
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…
DreamID: High-Fidelity and Fast diffusion-based Face Swapping via Triplet ID Group Learning
Fulong Ye, Miao Hua, Pengze Zhang +5
In this paper, we introduce DreamID, a diffusion-based face swapping model that achieves high levels of ID similarity, attribute preservation, image fidelity, and fast inference sp…
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…
AnyDressing: Customizable Multi-Garment Virtual Dressing via Latent Diffusion Models
Xinghui Li, Qichao Sun, Pengze Zhang +5
Recent advances in garment-centric image generation from text and image prompts based on diffusion models are impressive. However, existing methods lack support for various combina…
Tackling the Singularities at the Endpoints of Time Intervals in Diffusion Models
Pengze Zhang, Hubery Yin, Chen Li +1
Most diffusion models assume that the reverse process adheres to a Gaussian distribution. However, this approximation has not been rigorously validated, especially at singularities…
Formulating Discrete Probability Flow Through Optimal Transport
Pengze Zhang, Hubery Yin, Chen Li +1
Continuous diffusion models are commonly acknowledged to display a deterministic probability flow, whereas discrete diffusion models do not. In this paper, we aim to establish the…