🧑‍💻Project: rectified-pointflow.github.io
🔖Paper: arxiv.org/pdf/2506.05282
💻Code: github.com/GradientSpac...

This is a joint work with Tao Sun, Shengyu Huang, Shuran Song and @ir0armeni.bsky.social

Leveraging a conditional generative model, our model uncovers and learns shape symmetry and part interchangeability. As a result, it generalizes across categories and datasets, achieving SoTA performance across multiple benchmarks.

RPF directly generates the assembled-state point clouds from unposed 3D parts, enabling pose estimation entirely from shape, without correspondence learning, pose regression, or symmetry labels.

This is a joint work with the amazing team: Shengqu Cai, Shengyu Huang, Gordon Wetzstein, Naji Khosravan and @ir0armeni.bsky.social. See you in Vancouver!