activity
20142024
most citedPixelNet: Towards a General Pixel-level Architecture

55 citations · 162 across the 22 of their papers we have counts for

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Showing 2023Show all

11 papers · 1 filter

cs.CV2023

Lidar Panoptic Segmentation and Tracking without Bells and Whistles

Abhinav Agarwalla, Xuhua Huang, Jason Ziglar +5

State-of-the-art lidar panoptic segmentation (LPS) methods follow bottom-up segmentation-centric fashion wherein they build upon semantic segmentation networks by utilizing cluster…

cs.CV2023

Streaming Motion Forecasting for Autonomous Driving

Ziqi Pang, Deva Ramanan, Mengtian Li +1

Trajectory forecasting is a widely-studied problem for autonomous navigation. However, existing benchmarks evaluate forecasting based on independent snapshots of trajectories, whic…

cs.CV20235 cited

Dynamic 3D Gaussians: Tracking by Persistent Dynamic View Synthesis

Jonathon Luiten, Georgios Kopanas, Bastian Leibe +1

We present a method that simultaneously addresses the tasks of dynamic scene novel-view synthesis and six degree-of-freedom (6-DOF) tracking of all dense scene elements. We follow…

cs.CV20233 cited

Learning Lightweight Object Detectors via Multi-Teacher Progressive Distillation

Shengcao Cao, Mengtian Li, James Hays +3

Resource-constrained perception systems such as edge computing and vision-for-robotics require vision models to be both accurate and lightweight in computation and memory usage. Wh…

cs.CV2023

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)…

cs.CV20233 cited

WEDGE: A multi-weather autonomous driving dataset built from generative vision-language models

Aboli Marathe, Deva Ramanan, Rahee Walambe +1

The open road poses many challenges to autonomous perception, including poor visibility from extreme weather conditions. Models trained on good-weather datasets frequently fail at…