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 1021–1030 of 1576 papers

TitleStatusHype
MaskBEV: Towards A Unified Framework for BEV Detection and Map Segmentation—0
MBDF-Net: Multi-Branch Deep Fusion Network for 3D Object Detection—0
MDS-Net: A Multi-scale Depth Stratification Based Monocular 3D Object Detection Algorithm—0
MetaBEV: Solving Sensor Failures for 3D Detection and Map Segmentation—0
Methodology for a Statistical Analysis of Influencing Factors on 3D Object Detection Performance—0
Minkowski Tracker: A Sparse Spatio-Temporal R-CNN for Joint Object Detection and Tracking—0
Mitigating Perspective Distortion-induced Shape Ambiguity in Image Crops—0
MLF-DET: Multi-Level Fusion for Cross-Modal 3D Object Detection—0
MLOD: A multi-view 3D object detection based on robust feature fusion method—0
MMDR: A Result Feature Fusion Object Detection Approach for Autonomous System—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