6 papers
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)…
: a Steerable Generalist Robotic Foundation Model with Emergent Capabilities
Physical Intelligence, Bo Ai, Ali Amin +85
We present a new robotic foundation model, called , that can enable strong out-of-the-box performance in a wide range of scenarios. can follow diverse language…
MEM: Multi-Scale Embodied Memory for Vision Language Action Models
Marcel Torne, Karl Pertsch, Homer Walke +14
Conventionally, memory in end-to-end robotic learning involves inputting a sequence of past observations into the learned policy. However, in complex multi-stage real-world tasks,…
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…
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…
Toward Scalable, Flexible Scene Flow for Point Clouds
Kyle Vedder
Scene flow estimation is the task of describing 3D motion between temporally successive observations. This thesis aims to build the foundation for building scene flow estimators wi…