SOTAVerified

3D Object Detection

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 )

Papers

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Showing 1251–1260 of 1576 papers

TitleStatusHype
Dense Voxel Fusion for 3D Object Detection—0
Cyber Mobility Mirror: A Deep Learning-based Real-World Object Perception Platform Using Roadside LiDAR—0
Deep Camera Pose Regression Using Pseudo-LiDAR—0
Towards Safe, Real-Time Systems: Stereo vs Images and LiDAR for 3D Object Detection—0
Comparative study of 3D object detection frameworks based on LiDAR data and sensor fusion techniques—0
Semi-supervised 3D Object Detection via Temporal Graph Neural Networks—0
Survey and Systematization of 3D Object Detection Models and Methods—0
AutoAlign: Pixel-Instance Feature Aggregation for Multi-Modal 3D Object Detection—0
DeepMix: Mobility-aware, Lightweight, and Hybrid 3D Object Detection for Headsets—0
MDS-Net: A Multi-scale Depth Stratification Based Monocular 3D Object Detection Algorithm—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1EA-LSSNDS0.78—Unverified
2MMFusion-eNDS0.77—Unverified
3MegFusionNDS0.77—Unverified
4RacoonPowerNDS0.76—Unverified
5BEVFusion-eNDS0.76—Unverified
6DeepInteraction-largeNDS0.76—Unverified
7DeepInteraction-eNDS0.76—Unverified
8DAANDS0.75—Unverified
9FusionVPENDS0.75—Unverified
10CenterPoint-FusionNDS0.75—Unverified