3 papers
cs.CV2026
Muses: Designing, Composing, Generating Nonexistent Fantasy 3D Creatures without Training
Hexiao Lu, Xiaokun Sun, Zeyu Cai +4
We present Muses, the first training-free method for fantastic 3D creature generation in a feed-forward paradigm. Previous methods, which rely on part-aware optimization, manual as…
cs.CV2026
FlexAM: Flexible Appearance-Motion Decomposition for Versatile Video Generation Control
Mingzhi Sheng, Zekai Gu, Peng Li +4
Effective and generalizable control in video generation remains a significant challenge. While many methods rely on ambiguous or task-specific signals, we argue that a fundamental…
cs.CV2025
PDT: Point Distribution Transformation with Diffusion Models
Jionghao Wang, Cheng Lin, Yuan Liu +7
Point-based representations have consistently played a vital role in geometric data structures. Most point cloud learning and processing methods typically leverage the unordered an…