Due to the domain differences and unbalanced disparity distribution acro...
LiDAR devices are widely used in autonomous driving scenarios and resear...
LiDAR-based 3D Object detectors have achieved impressive performances in...
Dominated point cloud-based 3D object detectors in autonomous driving
sc...
Existing approaches for unsupervised point cloud pre-training are constr...
While fine-tuning pre-trained networks has become a popular way to train...
3D point cloud registration in remote sensing field has been greatly adv...
Even though considerable progress has been made in deep learning-based 3...
Existing deep learning-based approaches for monocular 3D object detectio...
Accurate detection of obstacles in 3D is an essential task for autonomou...
3D object detection is a key perception component in autonomous driving....
3D object detection from a single image is an important task in Autonomo...
To get clear street-view and photo-realistic simulation in autonomous
dr...
We present a novel approach to detect, segment, and reconstruct complete...
Despite the remarkable progresses made in deep-learning based depth map
...
Existing LiDAR-based 3D object detectors usually focus on the single-fra...
Conventional absolute camera pose via a Perspective-n-Point (PnP) solver...
In 2D/3D object detection task, Intersection-over-Union (IoU) has been w...
Recovering the absolute metric scale from a monocular camera is a challe...
Autonomous driving has attracted remarkable attention from both industry...
We present a LIDAR simulation framework that can automatically generate ...
3D point cloud generation by the deep neural network from a single image...
Scene parsing aims to assign a class (semantic) label for each pixel in ...
Large field-of-view fisheye lens cameras have attracted more and more
re...