Huan Ouyang

UniColorFlow: A Unified Framework for Multimodal-Guided Video Colorization with Consistency Flow

CaC: Advancing Video Reward Models via Hierarchical Spatiotemporal Concentrating

Concentrate and Concentrate (CaC) is a coarse-to-fine anomaly reward model based on Vision-Language Models that first conducts a global temporal scan to anchor anomalous time windows, then performs fine-grained spatial grounding within the localized interval, and finally derives robust judgments via structured spatiote...

Joint Alignment and Distillation for Video Generation via Sample-Guided Distribution Matching

DM-Align is introduced, which derives a complementary gradient direction to guide the model toward human-preferred samples, and eliminates the need for multi-step reward evaluation and complex ODE-SDE conversions inherent in traditional RL.