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 1361–1370 of 1576 papers

TitleStatusHype
RaCFormer: Towards High-Quality 3D Object Detection via Query-based Radar-Camera Fusion—0
RadarPillars: Efficient Object Detection from 4D Radar Point Clouds—0
R-AGNO-RPN: A LIDAR-Camera Region Deep Network for Resolution-Agnostic Detection—0
Range Adaptation for 3D Object Detection in LiDAR—0
RangeIoUDet: Range Image Based Real-Time 3D Object Detector Optimized by Intersection Over Union—0
RankDetNet: Delving Into Ranking Constraints for Object Detection—0
RayFormer: Improving Query-Based Multi-Camera 3D Object Detection via Ray-Centric Strategies—0
RCBEVDet++: Toward High-accuracy Radar-Camera Fusion 3D Perception Network—0
RC-BEVFusion: A Plug-In Module for Radar-Camera Bird's Eye View Feature Fusion—0
RCFusion: Fusing 4-D Radar and Camera With Bird’s-Eye View Features for 3-D Object Detection—0
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All datasetsnuScenesScanNetV2SUN-RGBD valKITTI Cars EasyKITTI Cars HardnuScenes Camera OnlyKITTI Cars Easy valKITTI Cars Moderate valnuscenes Camera-RadarView-of-Delft (val)KITTI Cars Hard valDAIR-V2X-I

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