12 papers
OmniDance: Multimodal Driven Dance Video Generation with Large-scale Internet Data
Kaixing Yang, Jiashu Zhu, Xulong Tang +8
Music-driven dance video generation aims to synthesize expressive human motion that is temporally aligned with music while maintaining high visual fidelity. Despite recent progress…
PRISM: Rethinking Atmospheric Scattering Reconstruction as a Unified Understanding and Restoration Model for Real-world Dehazing
Chengyu Fang, Chunming He, Yuelin Zhang +6
Real-world image dehazing (RID) aims to remove haze-induced degradation from real scenes. This task remains challenging due to non-uniform haze distribution, spatially varying colo…
Embedding-perturbed Exploration Preference Optimization for Flow Models
Sujie Hu, Chubin Chen, Jiashu Zhu +3
Recent advancements have established Reinforcement Learning (RL) as a pivotal paradigm for aligning generative models with human intent. However, group-based optimization framework…
MaTe: Images Are All You Need for Material Transfer via Diffusion Transformer
Nisha Huang, Henglin Liu, Yizhou Lin +5
Recent diffusion-based methods for material transfer rely on image fine-tuning or complex architectures with assistive networks, but face challenges including text dependency, extr…
ConceptWeaver: Weaving Disentangled Concepts with Flow
Jintao Chen, Aiming Hao, Xiaoqing Chen +6
Pre-trained flow-based models excel at synthesizing complex scenes yet lack a direct mechanism for disentangling and customizing their underlying concepts from one-shot real-world…
Taming Preference Mode Collapse via Directional Decoupling Alignment in Diffusion Reinforcement Learning
Chubin Chen, Sujie Hu, Jiashu Zhu +8
Recent studies have demonstrated significant progress in aligning text-to-image diffusion models with human preference via Reinforcement Learning from Human Feedback. However, whil…