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

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Showing 1151–1160 of 1576 papers

TitleStatusHype
ODAM: Object Detection, Association, and Mapping using Posed RGB VideoCode1
Deployment of Deep Neural Networks for Object Detection on Edge AI Devices with Runtime Optimization—0
RandomRooms: Unsupervised Pre-training from Synthetic Shapes and Randomized Layouts for 3D Object DetectionCode1
ST3D++: Denoised Self-training for Unsupervised Domain Adaptation on 3D Object Detection—0
Semi-supervised 3D Object Detection via Adaptive Pseudo-Labeling—0
SPG: Unsupervised Domain Adaptation for 3D Object Detection via Semantic Point Generation—0
PVT: Point-Voxel Transformer for Point Cloud LearningCode1
Is Pseudo-Lidar needed for Monocular 3D Object detection?Code1
Progressive Coordinate Transforms for Monocular 3D Object DetectionCode1
Fog Simulation on Real LiDAR Point Clouds for 3D Object Detection in Adverse WeatherCode1
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All datasetsnuScenesScanNetV2SUN-RGBD valKITTI Cars EasyKITTI Cars HardnuScenes Camera OnlyKITTI Cars Easy valKITTI Cars Moderate valnuscenes Camera-RadarView-of-Delft (val)KITTI Cars Hard valDAIR-V2X-I

Benchmark Results

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