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 1081–1090 of 1576 papers

TitleStatusHype
MonoDistill: Learning Spatial Features for Monocular 3D Object DetectionCode1
Survey and Systematization of 3D Object Detection Models and Methods—0
Attention-based Proposals Refinement for 3D Object DetectionCode1
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
End-To-End Optimization of LiDAR Beam Configuration for 3D Object Detection and LocalizationCode1
SASA: Semantics-Augmented Set Abstraction for Point-based 3D Object DetectionCode1
Rope3D: The Roadside Perception Dataset for Autonomous Driving and Monocular 3D Object Detection Task—0
SS3D: Sparsely-Supervised 3D Object Detection From Point Cloud—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