Computer Vision
 
Edit

3D Object Detection

585 papers with code • 55 benchmarks • 48 datasets

3D Object Detection is a task in computer vision where the goal is to identify and locate objects in a 3D environment based on their shape, location, and orientation. It involves detecting the presence of objects and determining their location in the 3D space in real-time. This task is crucial for applications such as autonomous vehicles, robotics, and augmented reality.

( Image credit: AVOD )

Libraries

Use these libraries to find 3D Object Detection models and implementations

Datasets

Subtasks

Most implemented papers

Most implemented Social Latest No code

YOLO9000: Better, Faster, Stronger

AlexeyAB/darknet • • CVPR 2017

On the 156 classes not in COCO, YOLO9000 gets 16. 0 mAP.

233
Paper
Code

Frustum PointNets for 3D Object Detection from RGB-D Data

charlesq34/frustum-pointnets • • CVPR 2018

In this work, we study 3D object detection from RGB-D data in both indoor and outdoor scenes.

68
Paper
Code

VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection

qianguih/voxelnet • • CVPR 2018

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.

44
Paper
Code

PointPillars: Fast Encoders for Object Detection from Point Clouds

nutonomy/second.pytorch • • CVPR 2019

These benchmarks suggest that PointPillars is an appropriate encoding for object detection in point clouds.

17
Paper
Code

nuScenes: A multimodal dataset for autonomous driving

nutonomy/nuscenes-devkit • CVPR 2020

Most autonomous vehicles, however, carry a combination of cameras and range sensors such as lidar and radar.

15
Paper
Code

PointRCNN: 3D Object Proposal Generation and Detection from Point Cloud

sshaoshuai/PointRCNN • • CVPR 2019

In this paper, we propose PointRCNN for 3D object detection from raw point cloud.

13
Paper
Code

Deep Hough Voting for 3D Object Detection in Point Clouds

facebookresearch/votenet • • ICCV 2019

Current 3D object detection methods are heavily influenced by 2D detectors.

13
Paper
Code

PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection

open-mmlab/OpenPCDet • • CVPR 2020

We present a novel and high-performance 3D object detection framework, named PointVoxel-RCNN (PV-RCNN), for accurate 3D object detection from point clouds.

12
Paper
Code

3D Bounding Box Estimation Using Deep Learning and Geometry

smallcorgi/3D-Deepbox • • CVPR 2017

In contrast to current techniques that only regress the 3D orientation of an object, our method first regresses relatively stable 3D object properties using a deep convolutional neural network and then combines these estimates with geometric constraints provided by a 2D object bounding box to produce a complete 3D bounding box.

11
Paper
Code

Center-based 3D Object Detection and Tracking

tianweiy/CenterPoint • • CVPR 2021

Three-dimensional objects are commonly represented as 3D boxes in a point-cloud.

11
Paper
Code
Contact us on: hello@paperswithcode.com . Papers With Code is a free resource with all data licensed under CC-BY-SA.
Terms Data policy Cookies policy