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 1271–1280 of 1576 papers

TitleStatusHype
SpikingRTNH: Spiking Neural Network for 4D Radar Object Detection—0
SpotNet: An Image Centric, Lidar Anchored Approach To Long Range Perception—0
SPOT: Scalable 3D Pre-training via Occupancy Prediction for Learning Transferable 3D Representations—0
SS3D: Single Shot 3D Object Detector—0
SS3D: Sparsely-Supervised 3D Object Detection From Point Cloud—0
SSC3OD: Sparsely Supervised Collaborative 3D Object Detection from LiDAR Point Clouds—0
SSF3D: Strict Semi-Supervised 3D Object Detection with Switching Filter—0
ST3D++: Denoised Self-training for Unsupervised Domain Adaptation on 3D Object Detection—0
STAL3D: Unsupervised Domain Adaptation for 3D Object Detection via Collaborating Self-Training and Adversarial Learning—0
StarNet: Targeted Computation for Object Detection in Point Clouds—0
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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