8 citations · 18 across the 26 of their papers we have counts for
5 papers · 1 filter
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…
Planning with Adaptive World Models for Autonomous Driving
Arun Balajee Vasudevan, Neehar Peri, Jeff Schneider +1
Motion planning is crucial for safe navigation in complex urban environments. Historically, motion planners (MPs) have been evaluated with procedurally-generated simulators like CA…
Shelf-Supervised Cross-Modal Pre-Training for 3D Object Detection
Mehar Khurana, Neehar Peri, James Hays +1
State-of-the-art 3D object detectors are often trained on massive labeled datasets. However, annotating 3D bounding boxes remains prohibitively expensive and time-consuming, partic…
Better Call SAL: Towards Learning to Segment Anything in Lidar
Aljoša Ošep, Tim Meinhardt, Francesco Ferroni +3
We propose the SAL (Segment Anything in Lidar) method consisting of a text-promptable zero-shot model for segmenting and classifying any object in Lidar, and a pseudo-labeling engi…
I Can't Believe It's Not Scene Flow!
Ishan Khatri, Kyle Vedder, Neehar Peri +2
Current scene flow methods broadly fail to describe motion on small objects, and current scene flow evaluation protocols hide this failure by averaging over many points, with most…