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 981–990 of 1576 papers

TitleStatusHype
LaserNet: An Efficient Probabilistic 3D Object Detector for Autonomous Driving—0
LCV2I: Communication-Efficient and High-Performance Collaborative Perception Framework with Low-Resolution LiDAR—0
Learned Fusion: 3D Object Detection using Calibration-Free Transformer Feature Fusion—0
Learned Multimodal Compression for Autonomous Driving—0
Learning 3D Perception from Others' Predictions—0
Learning Class Prototypes for Unified Sparse-Supervised 3D Object Detection—0
Multi-View Representation is What You Need for Point-Cloud Pre-Training—0
Learning Monocular 3D Vehicle Detection without 3D Bounding Box Labels—0
Learning Temporal Cues by Predicting Objects Move for Multi-camera 3D Object Detection—0
Learning to Evaluate Perception Models Using Planner-Centric Metrics—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