11 citations · 43 across the 12 of their papers we have counts for
6 papers · 1 filter
Voxel Transformer for 3D Object Detection
Jiageng Mao, Yujing Xue, Minzhe Niu +5
We present Voxel Transformer (VoTr), a novel and effective voxel-based Transformer backbone for 3D object detection from point clouds. Conventional 3D convolutional backbones in vo…
Pyramid R-CNN: Towards Better Performance and Adaptability for 3D Object Detection
Jiageng Mao, Minzhe Niu, Haoyue Bai +3
We present a flexible and high-performance framework, named Pyramid R-CNN, for two-stage 3D object detection from point clouds. Current approaches generally rely on the points or v…
NAS-OoD: Neural Architecture Search for Out-of-Distribution Generalization
Haoyue Bai, Fengwei Zhou, Lanqing Hong +3
Recent advances on Out-of-Distribution (OoD) generalization reveal the robustness of deep learning models against distribution shifts. However, existing works focus on OoD algorith…
OoD-Bench: Quantifying and Understanding Two Dimensions of Out-of-Distribution Generalization
Nanyang Ye, Kaican Li, Haoyue Bai +5
Deep learning has achieved tremendous success with independent and identically distributed (i.i.d.) data. However, the performance of neural networks often degenerates drastically…
Crowd Counting by Self-supervised Transfer Colorization Learning and Global Prior Classification
Haoyue Bai, Song Wen, S. -H. Gary Chan
Labeled crowd scene images are expensive and scarce. To significantly reduce the requirement of the labeled images, we propose ColorCount, a novel CNN-based approach by combining s…
Motion-guided Non-local Spatial-Temporal Network for Video Crowd Counting
Haoyue Bai, S. -H. Gary Chan
We study video crowd counting, which is to estimate the number of objects (people in this paper) in all the frames of a video sequence. Previous work on crowd counting is mostly on…