3D Object Detection
590 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 )
Benchmarks
These leaderboards are used to track progress in 3D Object Detection
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Libraries
Use these libraries to find 3D Object Detection models and implementations
KITTI
nuScenes
ScanNet
NYUv2
SUN RGB-D
S3DIS
Waymo Open Dataset
Argoverse
Argoverse 2
ONCE
Subtasks
Latest papers
CN-RMA: Combined Network with Ray Marching Aggregation for 3D Indoors Object Detection from Multi-view Images
This paper introduces CN-RMA, a novel approach for 3D indoor object detection from multi-view images.
Scalable Vision-Based 3D Object Detection and Monocular Depth Estimation for Autonomous Driving
owen-liuyuxuan/visionfactory
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Collectively, these contributions lay a robust foundation for the widespread adoption of vision-based 3D perception technologies in autonomous driving applications.
Leveraging Anchor-based LiDAR 3D Object Detection via Point Assisted Sample Selection
xjtu-haolin/point_assisted_sample_selection
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3D object detection based on LiDAR point cloud and prior anchor boxes is a critical technology for autonomous driving environment perception and understanding.
TUMTraf V2X Cooperative Perception Dataset
We propose CoopDet3D, a cooperative multi-modal fusion model, and TUMTraf-V2X, a perception dataset, for the cooperative 3D object detection and tracking task.
Sunshine to Rainstorm: Cross-Weather Knowledge Distillation for Robust 3D Object Detection
LiDAR-based 3D object detection models have traditionally struggled under rainy conditions due to the degraded and noisy scanning signals.
EMIFF: Enhanced Multi-scale Image Feature Fusion for Vehicle-Infrastructure Cooperative 3D Object Detection
bosszhe/vimi
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In autonomous driving, cooperative perception makes use of multi-view cameras from both vehicles and infrastructure, providing a global vantage point with rich semantic context of road conditions beyond a single vehicle viewpoint.
MultiCorrupt: A Multi-Modal Robustness Dataset and Benchmark of LiDAR-Camera Fusion for 3D Object Detection
Multi-modal 3D object detection models for automated driving have demonstrated exceptional performance on computer vision benchmarks like nuScenes.
AYDIV: Adaptable Yielding 3D Object Detection via Integrated Contextual Vision Transformer
Combining LiDAR and camera data has shown potential in enhancing short-distance object detection in autonomous driving systems.
Ray Denoising: Depth-aware Hard Negative Sampling for Multi-view 3D Object Detection
liewfeng/beam
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Multi-view 3D object detection systems often struggle with generating precise predictions due to the challenges in estimating depth from images, increasing redundant and incorrect detections.
ActiveAnno3D - An Active Learning Framework for Multi-Modal 3D Object Detection
We propose ActiveAnno3D, an active learning framework to select data samples for labeling that are of maximum informativeness for training.
