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 131–140 of 1576 papers

TitleStatusHype
Surface Representation for Point CloudsCode2
TJ4DRadSet: A 4D Radar Dataset for Autonomous DrivingCode2
Focal Sparse Convolutional Networks for 3D Object DetectionCode2
DAIR-V2X: A Large-Scale Dataset for Vehicle-Infrastructure Cooperative 3D Object DetectionCode2
Multi-Class Road User Detection With 3+1D Radar in the View-of-Delft DatasetCode2
Image-to-Lidar Self-Supervised Distillation for Autonomous Driving DataCode2
LiDAR Snowfall Simulation for Robust 3D Object DetectionCode2
MonoDETR: Depth-guided Transformer for Monocular 3D Object DetectionCode2
TransFusion: Robust LiDAR-Camera Fusion for 3D Object Detection with TransformersCode2
V2X-ViT: Vehicle-to-Everything Cooperative Perception with Vision TransformerCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1EA-LSSNDS0.78—Unverified
2MegFusionNDS0.77—Unverified
3MMFusion-eNDS0.77—Unverified
4DeepInteraction-largeNDS0.76—Unverified
5DeepInteraction-eNDS0.76—Unverified
6BEVFusion-eNDS0.76—Unverified
7RacoonPowerNDS0.76—Unverified
8ADS-TEAMNDS0.75—Unverified
9CenterPoint-FusionNDS0.75—Unverified
10UniTRNDS0.75—Unverified