95 citations · 338 across the 18 of their papers we have counts for
18 papers
Scene as Occupancy
Chonghao Sima, Wenwen Tong, Tai Wang +8
Human driver can easily describe the complex traffic scene by visual system. Such an ability of precise perception is essential for driver's planning. To achieve this, a geometry-a…
DORT: Modeling Dynamic Objects in Recurrent for Multi-Camera 3D Object Detection and Tracking
Qing Lian, Tai Wang, Dahua Lin +1
Recent multi-camera 3D object detectors usually leverage temporal information to construct multi-view stereo that alleviates the ill-posed depth estimation. However, they typically…
MV-JAR: Masked Voxel Jigsaw and Reconstruction for LiDAR-Based Self-Supervised Pre-Training
Runsen Xu, Tai Wang, Wenwei Zhang +4
This paper introduces the Masked Voxel Jigsaw and Reconstruction (MV-JAR) method for LiDAR-based self-supervised pre-training and a carefully designed data-efficient 3D object dete…
Position-Guided Point Cloud Panoptic Segmentation Transformer
Zeqi Xiao, Wenwei Zhang, Tai Wang +3
DEtection TRansformer (DETR) started a trend that uses a group of learnable queries for unified visual perception. This work begins by applying this appealing paradigm to LiDAR-bas…
GeoMIM: Towards Better 3D Knowledge Transfer via Masked Image Modeling for Multi-view 3D Understanding
Jihao Liu, Tai Wang, Boxiao Liu +3
Multi-view camera-based 3D detection is a challenging problem in computer vision. Recent works leverage a pretrained LiDAR detection model to transfer knowledge to a camera-based s…
Vision-Centric BEV Perception: A Survey
Yuexin Ma, Tai Wang, Xuyang Bai +7
In recent years, vision-centric Bird's Eye View (BEV) perception has garnered significant interest from both industry and academia due to its inherent advantages, such as providing…
MV-FCOS3D++: Multi-View Camera-Only 4D Object Detection with Pretrained Monocular Backbones
Tai Wang, Qing Lian, Chenming Zhu +2
In this technical report, we present our solution, dubbed MV-FCOS3D++, for the Camera-Only 3D Detection track in Waymo Open Dataset Challenge 2022. For multi-view camera-only 3D de…
Monocular 3D Object Detection with Depth from Motion
Tai Wang, Jiangmiao Pang, Dahua Lin
Perceiving 3D objects from monocular inputs is crucial for robotic systems, given its economy compared to multi-sensor settings. It is notably difficult as a single image can not p…
MonoDETR: Depth-guided Transformer for Monocular 3D Object Detection
Renrui Zhang, Han Qiu, Tai Wang +7
Monocular 3D object detection has long been a challenging task in autonomous driving. Most existing methods follow conventional 2D detectors to first localize object centers, and t…
Density-aware Chamfer Distance as a Comprehensive Metric for Point Cloud Completion
Tong Wu, Liang Pan, Junzhe Zhang +3
Chamfer Distance (CD) and Earth Mover's Distance (EMD) are two broadly adopted metrics for measuring the similarity between two point sets. However, CD is usually insensitive to mi…
Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR-based Perception
Xinge Zhu, Hui Zhou, Tai Wang +6
State-of-the-art methods for driving-scene LiDAR-based perception (including point cloud semantic segmentation, panoptic segmentation and 3D detection, \etc) often project the poin…
SIDE: Center-based Stereo 3D Detector with Structure-aware Instance Depth Estimation
Xidong Peng, Xinge Zhu, Tai Wang +1
3D detection plays an indispensable role in environment perception. Due to the high cost of commonly used LiDAR sensor, stereo vision based 3D detection, as an economical yet effec…
Probabilistic and Geometric Depth: Detecting Objects in Perspective
Tai Wang, Xinge Zhu, Jiangmiao Pang +1
3D object detection is an important capability needed in various practical applications such as driver assistance systems. Monocular 3D detection, as a representative general setti…
FCOS3D: Fully Convolutional One-Stage Monocular 3D Object Detection
Tai Wang, Xinge Zhu, Jiangmiao Pang +1
Monocular 3D object detection is an important task for autonomous driving considering its advantage of low cost. It is much more challenging than conventional 2D cases due to its i…
FLAVA: Find, Localize, Adjust and Verify to Annotate LiDAR-Based Point Clouds
Tai Wang, Conghui He, Zhe Wang +2
Recent years have witnessed the rapid progress of perception algorithms on top of LiDAR, a widely adopted sensor for autonomous driving systems. These LiDAR-based solutions are typ…
Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR Segmentation
Xinge Zhu, Hui Zhou, Tai Wang +5
State-of-the-art methods for large-scale driving-scene LiDAR segmentation often project the point clouds to 2D space and then process them via 2D convolution. Although this corpora…
SSN: Shape Signature Networks for Multi-class Object Detection from Point Clouds
Xinge Zhu, Yuexin Ma, Tai Wang +3
Multi-class 3D object detection aims to localize and classify objects of multiple categories from point clouds. Due to the nature of point clouds, i.e. unstructured, sparse and noi…
Reconfigurable Voxels: A New Representation for LiDAR-Based Point Clouds
Tai Wang, Xinge Zhu, Dahua Lin
LiDAR is an important method for autonomous driving systems to sense the environment. The point clouds obtained by LiDAR typically exhibit sparse and irregular distribution, thus p…