collaborators

6 papers

cs.CV2026

UniFlow: Zero-Shot LiDAR Scene Flow for Autonomous Vehicles

Siyi Li, Qingwen Zhang, Ishan Khatri +4

LiDAR scene flow is the task of estimating per-point 3D motion between consecutive point clouds. Recent methods achieve centimeter-level accuracy on popular autonomous vehicle (AV)…

cs.CV2026

UniPixie: Unified and Probabilistic 3D Physics Learning via Flow Matching

Qilin Huang, Quynh Anh Huynh, Long Le +5

Existing feed-forward networks excel at predicting a single set of physical properties from visual appearance, but this point-estimate paradigm fundamentally fails to capture the r…

cs.RO2026

OmniGuide: Universal Guidance Fields for Enhancing Generalist Robot Policies

Yunzhou Song, Long Le, Yong-Hyun Park +7

Vision-language-action(VLA) models have shown great promise as generalist policies for a large range of relatively simple tasks. However, they demonstrate limited performance on mo…

cs.CV2025

Neural Eulerian Scene Flow Fields

Kyle Vedder, Neehar Peri, Ishan Khatri +7

We reframe scene flow as the task of estimating a continuous space-time ODE that describes motion for an entire observation sequence, represented with a neural prior. Our method, E…

cs.CV2025

Pixie: Fast and Generalizable Supervised Learning of 3D Physics from Pixels

Long Le, Ryan Lucas, Chen Wang +4

Inferring the physical properties of 3D scenes from visual information is a critical yet challenging task for creating interactive and realistic virtual worlds. While humans intuit…

cs.CV2025

Articulate-Anything: Automatic Modeling of Articulated Objects via a Vision-Language Foundation Model

Long Le, Jason Xie, William Liang +7

Interactive 3D simulated objects are crucial in AR/VR, animations, and robotics, driving immersive experiences and advanced automation. However, creating these articulated objects…