7 papers
VPG: Visual Prefix Guidance for Autoregressive Image and Video Generation
Xinyao Liao, Qiyuan He, Yicong Li +4
Autoregressive image and video generators are trained with teacher-forced histories but must sample from their own generated prefixes at inference time, making them vulnerable to e…
RelaxFlow: Text-Driven Amodal 3D Generation
Jiayin Zhu, Guoji Fu, Xiaolu Liu +3
Image-to-3D generation faces inherent semantic ambiguity under occlusion, where partial observation alone is often insufficient to determine object category. In this work, we forma…
DynFlowDrive: Flow-Based Dynamic World Modeling for Autonomous Driving
Xiaolu Liu, Yicong Li, Song Wang +3
Recently, world models have been incorporated into the autonomous driving systems to improve the planning reliability. Existing approaches typically predict future states through a…
Interp3D: Correspondence-aware Interpolation for Generative Textured 3D Morphing
Xiaolu Liu, Yicong Li, Qiyuan He +4
Textured 3D morphing seeks to generate smooth and plausible transitions between two 3D assets, preserving both structural coherence and fine-grained appearance. This ability is cru…
VA-: Variational Policy Alignment for Pixel-Aware Autoregressive Generation
Xinyao Liao, Qiyuan He, Kai Xu +4
Autoregressive (AR) visual generation relies on tokenizers to map images to and from discrete sequences. However, tokenizers are trained to reconstruct clean images from ground-tru…
AnchorDS: Anchoring Dynamic Sources for Semantically Consistent Text-to-3D Generation
Jiayin Zhu, Linlin Yang, Yicong Li +1
Optimization-based text-to-3D methods distill guidance from 2D generative models via Score Distillation Sampling (SDS), but implicitly treat this guidance as static. This work show…