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 421–430 of 1576 papers

TitleStatusHype
ActiveAnno3D -- An Active Learning Framework for Multi-Modal 3D Object DetectionCode4
Improving Robustness of LiDAR-Camera Fusion Model against Weather Corruption from Fusion Strategy Perspective—0
RIDERS: Radar-Infrared Depth Estimation for Robust SensingCode1
A Survey for Foundation Models in Autonomous Driving—0
The Why, When, and How to Use Active Learning in Large-Data-Driven 3D Object Detection for Safe Autonomous Driving: An Empirical Exploration—0
SGV3D:Towards Scenario Generalization for Vision-based Roadside 3D Object DetectionCode1
LiDAR-PTQ: Post-Training Quantization for Point Cloud 3D Object DetectionCode2
MixSup: Mixed-grained Supervision for Label-efficient LiDAR-based 3D Object DetectionCode2
You Only Look Bottom-Up for Monocular 3D Object Detection—0
Pragmatic Communication in Multi-Agent Collaborative PerceptionCode0
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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