4 papers
Recover to Predict: Progressive Retrospective Learning for Variable-Length Trajectory Prediction
Hao Zhou, Lu Qi, Jason Li +5
Trajectory prediction is critical for autonomous driving, enabling safe and efficient planning in dense, dynamic traffic. Most existing methods optimize prediction accuracy under f…
TaPD: Temporal-adaptive Progressive Distillation for Observation-Adaptive Trajectory Forecasting in Autonomous Driving
Mingyu Fan, Yi Liu, Hao Zhou +3
Trajectory prediction is essential for autonomous driving, enabling vehicles to anticipate the motion of surrounding agents to support safe planning. However, most existing predict…
Enabling Versatile Controls for Video Diffusion Models
Xu Zhang, Hao Zhou, Haoming Qin +5
Despite substantial progress in text-to-video generation, achieving precise and flexible control over fine-grained spatiotemporal attributes remains a significant unresolved challe…
Erase Diffusion: Empowering Object Removal Through Calibrating Diffusion Pathways
Yi Liu, Hao Zhou, Wenxiang Shang +2
Erase inpainting, or object removal, aims to precisely remove target objects within masked regions while preserving the overall consistency of the surrounding content. Despite diff…