133 citations · 267 across the 11 of their papers we have counts for
11 papers · 1 filter
DeTra: A Unified Model for Object Detection and Trajectory Forecasting
Sergio Casas, Ben Agro, Jiageng Mao +4
The tasks of object detection and trajectory forecasting play a crucial role in understanding the scene for autonomous driving. These tasks are typically executed in a cascading ma…
CLIP: Contrastive Language-Image-Point Pretraining from Real-World Point Cloud Data
Yihan Zeng, Chenhan Jiang, Jiageng Mao +7
Contrastive Language-Image Pre-training, benefiting from large-scale unlabeled text-image pairs, has demonstrated great performance in open-world vision understanding tasks. Howeve…
3D Object Detection for Autonomous Driving: A Comprehensive Survey
Jiageng Mao, Shaoshuai Shi, Xiaogang Wang +1
Autonomous driving, in recent years, has been receiving increasing attention for its potential to relieve drivers' burdens and improve the safety of driving. In modern autonomous d…
Point2Seq: Detecting 3D Objects as Sequences
Yujing Xue, Jiageng Mao, Minzhe Niu +5
We present a simple and effective framework, named Point2Seq, for 3D object detection from point clouds. In contrast to previous methods that normally {predict attributes of 3D obj…
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…
SODA10M: A Large-Scale 2D Self/Semi-Supervised Object Detection Dataset for Autonomous Driving
Jianhua Han, Xiwen Liang, Hang Xu +8
Aiming at facilitating a real-world, ever-evolving and scalable autonomous driving system, we present a large-scale dataset for standardizing the evaluation of different self-super…
One Million Scenes for Autonomous Driving: ONCE Dataset
Jiageng Mao, Minzhe Niu, Chenhan Jiang +10
Current perception models in autonomous driving have become notorious for greatly relying on a mass of annotated data to cover unseen cases and address the long-tail problem. On th…
A Survey on Deep Learning-based Single Image Crowd Counting: Network Design, Loss Function and Supervisory Signal
Haoyue Bai, Jiageng Mao, S. -H. Gary Chan
Single image crowd counting is a challenging computer vision problem with wide applications in public safety, city planning, traffic management, etc. With the recent development of…
GRNet: Gridding Residual Network for Dense Point Cloud Completion
Haozhe Xie, Hongxun Yao, Shangchen Zhou +3
Estimating the complete 3D point cloud from an incomplete one is a key problem in many vision and robotics applications. Mainstream methods (e.g., PCN and TopNet) use Multi-layer P…
Interpolated Convolutional Networks for 3D Point Cloud Understanding
Jiageng Mao, Xiaogang Wang, Hongsheng Li
Point cloud is an important type of 3D representation. However, directly applying convolutions on point clouds is challenging due to the sparse, irregular and unordered data struct…