π§βπ»Project: rectified-pointflow.github.io
πPaper: arxiv.org/pdf/2506.05282
π»Code: github.com/GradientSpac...
This is a joint work with Tao Sun, Shengyu Huang, Shuran Song and @ir0armeni.bsky.social
@liyuanzzz.bsky.social
PhD student @ Stanford University. MS @ ETH Zurich. 3D Vision and Generation. https://www.zhuliyuan.net/
π§βπ»Project: rectified-pointflow.github.io
πPaper: arxiv.org/pdf/2506.05282
π»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.
07.07.2025 03:57 β π 1 π 0 π¬ 1 π 0RPF 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.
07.07.2025 03:57 β π 1 π 0 π¬ 1 π 0Point maps have become a powerful representation for image-based 3D reconstruction. What if we could push point maps even further to tackle 3D registration and assembly?
Introducing Rectified Point Flow (RPF), a generic formulation for point cloud pose estimation.
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!
27.05.2025 16:22 β π 1 π 0 π¬ 0 π 0π Want to redesign your apartment and control the style of every piece of furniture? (virtual try-on for 3D scenes).
π¨ Introducing ReStyle3D, a method that transforms your apartment into the design styles as you want! #stylization #SIGGRAPH
Page: restyle3d.github.io
Code: github.com/GradientSpac...
Glad to be selected as Outstanding Reviewer for CVPR25!
12.05.2025 05:11 β π 1 π 0 π¬ 0 π 0π¨ SLAM struggling in dynamic environments? We've been there.
WildGS-SLAM at #CVPR2025, our new monocular RGB SLAM system, tackles dynamic scenes with uncertainty-aware tracking and mapping, resulting to more robust tracking, cleaner maps, and high-quality view synthesis. β¬οΈ
π wildgs-slam.github.io
π Excited to share our latest work, CrossOver: 3D Scene Cross-Modal Alignment, accepted to #CVPR2025 πβ¨
We learn a unified, modality-agnostic embedding space, enabling seamless scene-level alignment across multiple modalities β no semantic annotations needed!π