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 791–800 of 1576 papers

TitleStatusHype
Deep Continuous Fusion for Multi-Sensor 3D Object Detection—0
Deep Fitting Degree Scoring Network for Monocular 3D Object Detection—0
DeepFusion: A Robust and Modular 3D Object Detector for Lidars, Cameras and Radars—0
DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection—0
Deep learning for 3D Object Detection and Tracking in Autonomous Driving: A Brief Survey—0
Deep Learning of Local RGB-D Patches for 3D Object Detection and 6D Pose Estimation—0
Deep Learning on Radar Centric 3D Object Detection—0
Deep Optics for Monocular Depth Estimation and 3D Object Detection—0
Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception—0
Deep SCNN-based Real-time Object Detection for Self-driving Vehicles Using LiDAR Temporal Data—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