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

Showing 561570 of 1576 papers

TitleStatusHype
GeoBEV: Learning Geometric BEV Representation for Multi-view 3D Object DetectionCode1
M3D-RPN: Monocular 3D Region Proposal Network for Object DetectionCode1
Attention-based Proposals Refinement for 3D Object DetectionCode1
FGFusion: Fine-Grained Lidar-Camera Fusion for 3D Object DetectionCode1
CN-RMA: Combined Network with Ray Marching Aggregation for 3D Indoor Object Detection from Multi-view ImagesCode1
MASS: Multi-Attentional Semantic Segmentation of LiDAR Data for Dense Top-View UnderstandingCode1
Improving 3D Object Detection with Channel-wise TransformerCode1
A Simple and Efficient Multi-task Network for 3D Object Detection and Road UnderstandingCode1
Mix-Teaching: A Simple, Unified and Effective Semi-Supervised Learning Framework for Monocular 3D Object DetectionCode1
CN-RMA: Combined Network with Ray Marching Aggregation for 3D Indoors Object Detection from Multi-view ImagesCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1EA-LSSNDS0.78Unverified
2MMFusion-eNDS0.77Unverified
3MegFusionNDS0.77Unverified
4RacoonPowerNDS0.76Unverified
5BEVFusion-eNDS0.76Unverified
6DeepInteraction-largeNDS0.76Unverified
7DeepInteraction-eNDS0.76Unverified
8DAANDS0.75Unverified
9FusionVPENDS0.75Unverified
10CenterPoint-FusionNDS0.75Unverified