9 citations · 12 across the 5 of their papers we have counts for
5 papers
Unsupervised 3D Perception with 2D Vision-Language Distillation for Autonomous Driving
Mahyar Najibi, Jingwei Ji, Yin Zhou +4
Closed-set 3D perception models trained on only a pre-defined set of object categories can be inadequate for safety critical applications such as autonomous driving where new objec…
MoDAR: Using Motion Forecasting for 3D Object Detection in Point Cloud Sequences
Yingwei Li, Charles R. Qi, Yin Zhou +2
Occluded and long-range objects are ubiquitous and challenging for 3D object detection. Point cloud sequence data provide unique opportunities to improve such cases, as an occluded…
VPU-EM: An Event-based Modeling Framework to Evaluate NPU Performance and Power Efficiency at Scale
Charles Qi, Yi Wang, Hui Wang +18
State-of-art NPUs are typically architected as a self-contained sub-system with multiple heterogeneous hardware computing modules, and a dataflow-driven programming model. There la…
Multi-modal 3D Human Pose Estimation with 2D Weak Supervision in Autonomous Driving
Jingxiao Zheng, Xinwei Shi, Alexander Gorban +9
3D human pose estimation (HPE) in autonomous vehicles (AV) differs from other use cases in many factors, including the 3D resolution and range of data, absence of dense depth maps,…
Revisiting 3D Object Detection From an Egocentric Perspective
Boyang Deng, Charles R. Qi, Mahyar Najibi +3
3D object detection is a key module for safety-critical robotics applications such as autonomous driving. For these applications, we care most about how the detections affect the e…