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 941–950 of 1576 papers

TitleStatusHype
ContrastAlign: Toward Robust BEV Feature Alignment via Contrastive Learning for Multi-Modal 3D Object Detection—0
Cooper: Cooperative Perception for Connected Autonomous Vehicles based on 3D Point Clouds—0
CornerPoint3D: Look at the Nearest Corner Instead of the Center—0
CorrBEV: Multi-View 3D Object Detection by Correlation Learning with Multi-modal Prototypes—0
Cost-Aware Evaluation and Model Scaling for LiDAR-Based 3D Object Detection—0
CP-VoteNet: Contrastive Prototypical VoteNet for Few-Shot Point Cloud Object Detection—0
CRAFT: Camera-Radar 3D Object Detection with Spatio-Contextual Fusion Transformer—0
CramNet: Camera-Radar Fusion with Ray-Constrained Cross-Attention for Robust 3D Object Detection—0
CRKD: Enhanced Camera-Radar Object Detection with Cross-modality Knowledge Distillation—0
Cross-Cluster Shifting for Efficient and Effective 3D Object Detection in Autonomous Driving—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