209 citations · 917 across the 34 of their papers we have counts for
51 papers · 1 filter
Lidar Panoptic Segmentation in an Open World
Anirudh S Chakravarthy, Meghana Reddy Ganesina, Peiyun Hu +4
Addressing Lidar Panoptic Segmentation (LPS ) is crucial for safe deployment of autonomous vehicles. LPS aims to recognize and segment lidar points w.r.t. a pre-defined vocabulary…
Learning to Discover and Detect Objects
Vladimir Fomenko, Ismail Elezi, Deva Ramanan +2
We tackle the problem of novel class discovery and localization (NCDL). In this setting, we assume a source dataset with supervision for only some object classes. Instances of othe…
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…
Differentiable Raycasting for Self-supervised Occupancy Forecasting
Tarasha Khurana, Peiyun Hu, Achal Dave +3
Motion planning for safe autonomous driving requires learning how the environment around an ego-vehicle evolves with time. Ego-centric perception of driveable regions in a scene no…
Forecasting from LiDAR via Future Object Detection
Neehar Peri, Jonathon Luiten, Mengtian Li +3
Object detection and forecasting are fundamental components of embodied perception. These two problems, however, are largely studied in isolation by the community. In this paper, w…
Long-Tailed Recognition via Weight Balancing
Shaden Alshammari, Yu-Xiong Wang, Deva Ramanan +1
In the real open world, data tends to follow long-tailed class distributions, motivating the well-studied long-tailed recognition (LTR) problem. Naive training produces models that…