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

Showing 361370 of 1576 papers

TitleStatusHype
Frustum-PointPillars: A Multi-Stage Approach for 3D Object Detection using RGB Camera and LiDARCode1
Densely Constrained Depth Estimator for Monocular 3D Object DetectionCode1
AutoAlignV2: Deformable Feature Aggregation for Dynamic Multi-Modal 3D Object DetectionCode1
Density-Insensitive Unsupervised Domain Adaption on 3D Object DetectionCode1
BEV-LGKD: A Unified LiDAR-Guided Knowledge Distillation Framework for BEV 3D Object DetectionCode1
Learning to Detect Objects from Multi-Agent LiDAR Scans without Manual LabelsCode1
CR3DT: Camera-RADAR Fusion for 3D Detection and TrackingCode1
BEV-MAE: Bird's Eye View Masked Autoencoders for Point Cloud Pre-training in Autonomous Driving ScenariosCode1
BEVNeXt: Reviving Dense BEV Frameworks for 3D Object DetectionCode1
Fooling LiDAR Perception via Adversarial Trajectory PerturbationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1EA-LSSNDS0.78Unverified
2MMFusion-eNDS0.77Unverified
3MegFusionNDS0.77Unverified
4RacoonPowerNDS0.76Unverified
5BEVFusion-eNDS0.76Unverified
6DeepInteraction-largeNDS0.76Unverified
7DeepInteraction-eNDS0.76Unverified
8DAANDS0.75Unverified
9FusionVPENDS0.75Unverified
10CenterPoint-FusionNDS0.75Unverified