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 461470 of 1576 papers

TitleStatusHype
Pyramid R-CNN: Towards Better Performance and Adaptability for 3D Object DetectionCode1
Voxel Transformer for 3D Object DetectionCode1
4D-Net for Learned Multi-Modal AlignmentCode1
Spatio-temporal Self-Supervised Representation Learning for 3D Point CloudsCode1
AutoShape: Real-Time Shape-Aware Monocular 3D Object DetectionCode1
ODAM: Object Detection, Association, and Mapping using Posed RGB VideoCode1
Improving 3D Object Detection with Channel-wise TransformerCode1
RandomRooms: Unsupervised Pre-training from Synthetic Shapes and Randomized Layouts for 3D Object DetectionCode1
Is Pseudo-Lidar needed for Monocular 3D Object detection?Code1
PVT: Point-Voxel Transformer for Point Cloud LearningCode1
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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