Register Any Point: Scaling 3D Point Cloud Registration by Flow Matching
A single flow-matching model for pairwise and multi-view registration, generalizing across scene scales and sensor modalities.
Publications
Google Scholar* Equal contribution
2026
Energy-based Compositional Diffusion Planning
Composing short trajectory fragments into coherent long-horizon robot plans with a global energy and consistent boundary corrections.
Do 3D Large Language Models Really Understand 3D Spatial Relationships?
Exposing language shortcuts in 3D reasoning benchmarks and introducing Real-3DQA to test whether models actually use visual geometry.
ARC: A Reasoning Recipe for Robot Foundation Models
Action-grounded causal reasoning improves robot foundation models using automatically labeled existing demonstrations.
FAMOS: Feed-Forward 3D Articulation Modeling from Sparse Observations
A feed-forward model that predicts movable parts and joint parameters of articulated objects from a sparse, unordered set of partial point clouds.
2025
Rectified Point Flow: Generic Point Cloud Pose Estimation
One generative formulation for point cloud registration and multi-part assembly, learning geometric symmetries without symmetry labels.
Seed1.5-Thinking: Advancing Superb Reasoning Models with Reinforcement Learning
Scaling reasoning through reinforcement learning, with advances in training data, reward modeling, algorithms, and distributed infrastructure.
Nothing Stands Still: A Spatiotemporal Benchmark on 3D Point Cloud Registration Under Large Geometric and Temporal Change
A real-world benchmark for aligning 3D scenes across construction and renovation, with large structural and temporal changes.
2022
On the Practicality of Deterministic Epistemic Uncertainty
Testing whether deterministic uncertainty estimates remain reliable under distribution shifts and in dense prediction tasks.
2019
Leveraging Crowdsourced GPS Data for Road Extraction From Aerial Imagery
Leveraging crowdsourced GPS data to improve and support road extraction from aerial imagery.
2018
Combining Satellite Imagery and GPS Data for Road Extraction
Combining satellite imagery with GPS data to improve road extraction quality
Stacked U-Nets with Multi-output for Road Extraction
Stacked U-Nets, auxiliary supervision, and topology-aware post-processing for extracting connected roads from satellite imagery.