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 361370 of 1576 papers

TitleStatusHype
3DPPE: 3D Point Positional Encoding for Multi-Camera 3D Object Detection TransformersCode1
3D Dual-Fusion: Dual-Domain Dual-Query Camera-LiDAR Fusion for 3D Object DetectionCode1
Sparse2Dense: Learning to Densify 3D Features for 3D Object DetectionCode1
AeDet: Azimuth-invariant Multi-view 3D Object DetectionCode1
aiMotive Dataset: A Multimodal Dataset for Robust Autonomous Driving with Long-Range PerceptionCode1
BEVDistill: Cross-Modal BEV Distillation for Multi-View 3D Object DetectionCode1
3D Cascade RCNN: High Quality Object Detection in Point CloudsCode1
Cross-Modality Knowledge Distillation Network for Monocular 3D Object DetectionCode1
Robust Collaborative 3D Object Detection in Presence of Pose ErrorsCode1
Point-DAE: Denoising Autoencoders for Self-supervised Point Cloud LearningCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1EA-LSSNDS0.78Unverified
2MegFusionNDS0.77Unverified
3MMFusion-eNDS0.77Unverified
4BEVFusion-eNDS0.76Unverified
5RacoonPowerNDS0.76Unverified
6DeepInteraction-largeNDS0.76Unverified
7DeepInteraction-eNDS0.76Unverified
8FusionVPENDS0.75Unverified
9FocalFormer3D-FNDS0.75Unverified
10CenterPoint-FusionNDS0.75Unverified