33 citations · 39 across the 6 of their papers we have counts for
19 papers
Improving the Intra-class Long-tail in 3D Detection via Rare Example Mining
Chiyu Max Jiang, Mahyar Najibi, Charles R. Qi +2
Continued improvements in deep learning architectures have steadily advanced the overall performance of 3D object detectors to levels on par with humans for certain tasks and datas…
Motion Inspired Unsupervised Perception and Prediction in Autonomous Driving
Mahyar Najibi, Jingwei Ji, Yin Zhou +4
Learning-based perception and prediction modules in modern autonomous driving systems typically rely on expensive human annotation and are designed to perceive only a handful of pr…
Offboard 3D Object Detection from Point Cloud Sequences
Charles R. Qi, Yin Zhou, Mahyar Najibi +4
While current 3D object recognition research mostly focuses on the real-time, onboard scenario, there are many offboard use cases of perception that are largely under-explored, suc…
Scale Normalized Image Pyramids with AutoFocus for Object Detection
Bharat Singh, Mahyar Najibi, Abhishek Sharma +1
We present an efficient foveal framework to perform object detection. A scale normalized image pyramid (SNIP) is generated that, like human vision, only attends to objects within a…
ASAP-NMS: Accelerating Non-Maximum Suppression Using Spatially Aware Priors
Rohun Tripathi, Vasu Singla, Mahyar Najibi +3
The widely adopted sequential variant of Non Maximum Suppression (or Greedy-NMS) is a crucial module for object-detection pipelines. Unfortunately, for the region proposal stage of…
DOPS: Learning to Detect 3D Objects and Predict their 3D Shapes
Mahyar Najibi, Guangda Lai, Abhijit Kundu +7
We propose DOPS, a fast single-stage 3D object detection method for LIDAR data. Previous methods often make domain-specific design decisions, for example projecting points into a b…