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 721–730 of 1576 papers

TitleStatusHype
Boosting Deep Neural Networks with Geometrical Prior Knowledge: A Survey—0
Distance-Normalized Unified Representation for Monocular 3D Object Detection—0
Moby: Empowering 2D Models for Efficient Point Cloud Analytics on the Edge—0
MambaBEV: An efficient 3D detection model with Mamba2—0
MapFusion: A General Framework for 3D Object Detection with HDMaps—0
Disentangling Monocular 3D Object Detection—0
Disentangling and Vectorization: A 3D Visual Perception Approach for Autonomous Driving Based on Surround-View Fisheye Cameras—0
Boosting 3D Object Detection by Simulating Multimodality on Point Clouds—0
A Light Perspective for 3D Object Detection—0
DisARM: Displacement Aware Relation Module for 3D Detection—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