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 1231–1240 of 1576 papers

TitleStatusHype
Cost-Aware Evaluation and Model Scaling for LiDAR-Based 3D Object Detection—0
Rotationally Equivariant 3D Object Detection—0
Unsupervised Domain Adaptation for Monocular 3D Object Detection via Self-Training—0
Graph-DETR3D: Rethinking Overlapping Regions for Multi-View 3D Object Detection—0
Shape-Aware Monocular 3D Object Detection—0
Multi-Camera Multiple 3D Object Tracking on the Move for Autonomous Vehicles—0
HyperDet3D: Learning a Scene-conditioned 3D Object Detector—0
M^2BEV: Multi-Camera Joint 3D Detection and Segmentation with Unified Birds-Eye View Representation—0
CAT-Det: Contrastively Augmented Transformer for Multi-modal 3D Object Detection—0
Accelerating Federated Edge Learning via Topology Optimization—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