157 citations · 220 across the 15 of their papers we have counts for
18 papers · 1 filter
An Empirical Analysis of Range for 3D Object Detection
Neehar Peri, Mengtian Li, Benjamin Wilson +3
LiDAR-based 3D detection plays a vital role in autonomous navigation. Surprisingly, although autonomous vehicles (AVs) must detect both near-field objects (for collision avoidance)…
ZeroFlow: Scalable Scene Flow via Distillation
Kyle Vedder, Neehar Peri, Nathaniel Chodosh +6
Scene flow estimation is the task of describing the 3D motion field between temporally successive point clouds. State-of-the-art methods use strong priors and test-time optimizatio…
Far3Det: Towards Far-Field 3D Detection
Shubham Gupta, Jeet Kanjani, Mengtian Li +4
We focus on the task of far-field 3D detection (Far3Det) of objects beyond a certain distance from an observer, e.g., 50m. Far3Det is particularly important for autonomous vehic…
PVA: Pixel-aligned Volumetric Avatars
Amit Raj, Michael Zollhoefer, Tomas Simon +4
Acquisition and rendering of photo-realistic human heads is a highly challenging research problem of particular importance for virtual telepresence. Currently, the highest quality…
ANR: Articulated Neural Rendering for Virtual Avatars
Amit Raj, Julian Tanke, James Hays +3
The combination of traditional rendering with neural networks in Deferred Neural Rendering (DNR) provides a compelling balance between computational complexity and realism of the r…
Scene Flow from Point Clouds with or without Learning
Jhony Kaesemodel Pontes, James Hays, Simon Lucey
Scene flow is the three-dimensional (3D) motion field of a scene. It provides information about the spatial arrangement and rate of change of objects in dynamic environments. Curre…