6 papers
Joint Alignment and Distillation for Video Generation via Sample-Guided Distribution Matching
Jiuzhou Lin, Junlong Wu, Fei Zuo +11
Aligning video generative models to human preferences heavily relies on Reinforcement Learning (RL), which suffers from extensive computational overhead. Existing workflows typical…
Step Back to Move Forward: Reflection-Aware Preference Optimization for Visual Generation
Junlong Wu, Jiuzhou Lin, Jia Sun +7
Diffusion models have become the mainstream paradigm for modern visual generation and have substantially advanced multimedia content synthesis, especially in text-to-image and text…
TextRefine: Improving Textual Fidelity, Spatial Placement, and Glyph Rendering for Text Editing in Product Posters
Honglie Wang, Jia Sun, Zijun Li +11
Text editing in product posters entails inserting new text or replacing existing text while preserving product appearance, background content, and global composition. Despite recen…
DetailAnywhere: Fashion Detail Generation via Cross-Modal Feature Alignment Distillation
Zijun Li, Yimin Zhou, Jia Sun +12
Diffusion-based generative AI has achieved remarkable success in e-commerce applications such as virtual try-on, poster generation, and product background synthesis. However, when…
CaC: Advancing Video Reward Models via Hierarchical Spatiotemporal Concentrating
Jiyuan Wang, Huan Ouyang, Jiuzhou Lin +15
In this paper, we propose Concentrate and Concentrate (CaC), a coarse-to-fine anomaly reward model based on Vision-Language Models. During inference, it first conducts a global tem…
OmniDiT: Extending Diffusion Transformer to Omni-VTON Framework
Weixuan Zeng, Pengcheng Wei, Huaiqing Wang +8
Despite the rapid advancement of Virtual Try-On (VTON) and Try-Off (VTOFF) technologies, existing VTON methods face challenges with fine-grained detail preservation, generalization…