4 papers
ViPO: Visual Preference Optimization at Scale
Ming Li, Jie Wu, Justin Cui +3
While preference optimization is crucial for improving visual generative models, how to effectively scale this paradigm remains largely unexplored. Current open-source preference d…
Learning from Noisy Preferences: A Semi-Supervised Learning Approach to Direct Preference Optimization
Xinxin Liu, Ming Li, Zonglin Lyu +2
Human visual preferences are inherently multi-dimensional, encompassing aesthetics, detail fidelity, and semantic alignment. However, existing datasets provide only single, holisti…
CPO: Condition Preference Optimization for Controllable Image Generation
Zonglin Lyu, Ming Li, Xinxin Liu +1
To enhance controllability in text-to-image generation, ControlNet introduces image-based control signals, while ControlNet++ improves pixel-level cycle consistency between generat…
TLB-VFI: Temporal-Aware Latent Brownian Bridge Diffusion for Video Frame Interpolation
Zonglin Lyu, Chen Chen
Video Frame Interpolation (VFI) aims to predict the intermediate frame (we use n to denote time in videos to avoid notation overload with the timestep in diffusion models…