3D Object Detection From Stereo Images

12 papers with code • 3 benchmarks • 4 datasets

Estimating oriented 3D bounding boxes from Stereo Cameras only.

Image: You et al

Most implemented papers

Stereo R-CNN based 3D Object Detection for Autonomous Driving

HKUST-Aerial-Robotics/Stereo-RCNN CVPR 2019

Our method, called Stereo R-CNN, extends Faster R-CNN for stereo inputs to simultaneously detect and associate object in left and right images.

Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving

mileyan/pseudo_lidar CVPR 2019

However, in this paper we argue that it is not the quality of the data but its representation that accounts for the majority of the difference.

Triangulation Learning Network: from Monocular to Stereo 3D Object Detection

Zengyi-Qin/TLNet CVPR 2019

In this paper, we study the problem of 3D object detection from stereo images, in which the key challenge is how to effectively utilize stereo information.

Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving

mileyan/Pseudo_Lidar_V2 ICLR 2020

In this paper we provide substantial advances to the pseudo-LiDAR framework through improvements in stereo depth estimation.

DSGN: Deep Stereo Geometry Network for 3D Object Detection

chenyilun95/DSGN CVPR 2020

Most state-of-the-art 3D object detectors heavily rely on LiDAR sensors because there is a large performance gap between image-based and LiDAR-based methods.

Disp R-CNN: Stereo 3D Object Detection via Shape Prior Guided Instance Disparity Estimation

zju3dv/disprcnn CVPR 2020

In this paper, we propose a novel system named Disp R-CNN for 3D object detection from stereo images.

3D-ZeF: A 3D Zebrafish Tracking Benchmark Dataset

mapeAAU/3D-ZeF CVPR 2020

In this work we present a novel publicly available stereo based 3D RGB dataset for multi-object zebrafish tracking, called 3D-ZeF.

Wasserstein Distances for Stereo Disparity Estimation

Div99/W-Stereo-Disp NeurIPS 2020

Existing approaches to depth or disparity estimation output a distribution over a set of pre-defined discrete values.

PLUMENet: Efficient 3D Object Detection from Stereo Images

meteorshowers/X-StereoLab 17 Jan 2021

In this paper we propose a model that unifies these two tasks and performs them in the same metric space.

YOLOStereo3D: A Step Back to 2D for Efficient Stereo 3D Detection

Owen-Liuyuxuan/visualDet3D 17 Mar 2021

Object detection in 3D with stereo cameras is an important problem in computer vision, and is particularly crucial in low-cost autonomous mobile robots without LiDARs.