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 841850 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
UpCycling: Semi-supervised 3D Object Detection without Sharing Raw-level Unlabeled Scenes0
Transformation-Equivariant 3D Object Detection for Autonomous Driving0
AeDet: Azimuth-invariant Multi-view 3D Object DetectionCode1
PointCLIP V2: Prompting CLIP and GPT for Powerful 3D Open-world LearningCode2
Context-Aware Data Augmentation for LIDAR 3D Object Detection0
Sparse4D: Multi-view 3D Object Detection with Sparse Spatial-Temporal FusionCode2
BEVFormer v2: Adapting Modern Image Backbones to Bird's-Eye-View Recognition via Perspective SupervisionCode4
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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