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 671–680 of 1576 papers

TitleStatusHype
OriCon3D: Effective 3D Object Detection using Orientation and Confidence—0
HyperMODEST: Self-Supervised 3D Object Detection with Confidence Score FilteringCode0
Gradient-based Maximally Interfered Retrieval for Domain Incremental 3D Object DetectionCode0
SparseFusion: Fusing Multi-Modal Sparse Representations for Multi-Sensor 3D Object DetectionCode2
Group Equivariant BEV for 3D Object Detection—0
DQS3D: Densely-matched Quantization-aware Semi-supervised 3D DetectionCode1
Transformer-based stereo-aware 3D object detection from binocular images—0
Fully Sparse Fusion for 3D Object DetectionCode1
Once Detected, Never Lost: Surpassing Human Performance in Offline LiDAR based 3D Object Detection—0
MMDR: A Result Feature Fusion Object Detection Approach for Autonomous System—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