3D Object Detection
3D object detection classifies the object category and estimates oriented 3D bounding boxes of physical objects from 3D sensor data.
Leaderboards
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Greatest papers with code
Frustum PointNets for 3D Object Detection from RGB-D Data
CVPR 2018
• charlesq34/pointnet
• 
In this work, we study 3D object detection from RGB-D data in both indoor and outdoor scenes.
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
CVPR 2018
• charlesq34/pointnet
•
Accurate detection of objects in 3D point clouds is a central problem in many applications, such as autonomous navigation, housekeeping robots, and augmented/virtual reality.
3D OBJECT DETECTION AUTONOMOUS NAVIGATION FEATURE ENGINEERING OBJECT LOCALIZATION
PointRCNN: 3D Object Proposal Generation and Detection from Point Cloud
CVPR 2019
• sshaoshuai/PointRCNN
• 
In this paper, we propose PointRCNN for 3D object detection from raw point cloud.
nuScenes: A multimodal dataset for autonomous driving
• traveller59/second.pytorch
•
In this work we present nuTonomy scenes (nuScenes), the first dataset to carry the full autonomous vehicle sensor suite: 6 cameras, 5 radars and 1 lidar, all with full 360 degree field of view.
SOTA for 3D Object Detection on nuScenes
Deep Hough Voting for 3D Object Detection in Point Clouds
ICCV 2019
• facebookresearch/votenet
•
Current 3D object detection methods are heavily influenced by 2D detectors.
SOTA for 3D Object Detection on SUN-RGBD
Joint 3D Proposal Generation and Object Detection from View Aggregation
• kujason/avod
•
We present AVOD, an Aggregate View Object Detection network for autonomous driving scenarios.
#2 best model for
3D Object Detection
on KITTI Cars Hard
Stereo R-CNN based 3D Object Detection for Autonomous Driving
CVPR 2019
• HKUST-Aerial-Robotics/Stereo-RCNN
•
Our method, called Stereo R-CNN, extends Faster R-CNN for stereo inputs to simultaneously detect and associate object in left and right images.
SBNet: Sparse Blocks Network for Fast Inference
CVPR 2018
• uber/sbnet
•
Conventional deep convolutional neural networks (CNNs) apply convolution operators uniformly in space across all feature maps for hundreds of layers - this incurs a high computational cost for real-time applications.
3D OBJECT DETECTION OBJECT CLASSIFICATION SEMANTIC SEGMENTATION
Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving
CVPR 2019
• mileyan/pseudo_lidar
•
3D object detection is an essential task in autonomous driving.
BB8: A Scalable, Accurate, Robust to Partial Occlusion Method for Predicting the 3D Poses of Challenging Objects without Using Depth
ICCV 2017
• Microsoft/singleshotpose
•
We introduce a novel method for 3D object detection and pose estimation from color images only.
#6 best model for
6D Pose Estimation using RGB
on LineMOD