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 1271–1280 of 1576 papers

TitleStatusHype
Multi-View Attentive Contextualization for Multi-View 3D Object Detection—0
MutualForce: Mutual-Aware Enhancement for 4D Radar-LiDAR 3D Object Detection—0
Mutual Information Analysis in Multimodal Learning Systems—0
Mutual Information-calibrated Conformal Feature Fusion for Uncertainty-Aware Multimodal 3D Object Detection at the Edge—0
MV2DFusion: Leveraging Modality-Specific Object Semantics for Multi-Modal 3D Detection—0
MV-DETR: Multi-modality indoor object detection by Multi-View DEtecton TRansformers—0
MVFAN: Multi-View Feature Assisted Network for 4D Radar Object Detection—0
MVFusion: Multi-View 3D Object Detection with Semantic-aligned Radar and Camera Fusion—0
MVX-Net: Multimodal VoxelNet for 3D Object Detection—0
Nearest Neighbors Meet Deep Neural Networks for Point Cloud Analysis—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