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 1331–1340 of 1576 papers

TitleStatusHype
Towards Universal LiDAR-Based 3D Object Detection by Multi-Domain Knowledge Transfer—0
Towards Universal Physical Attacks On Cascaded Camera-Lidar 3D Object Detection Models—0
Traffic-Net: 3D Traffic Monitoring Using a Single Camera—0
TraIL-Det: Transformation-Invariant Local Feature Networks for 3D LiDAR Object Detection with Unsupervised Pre-Training—0
Training an Open-Vocabulary Monocular 3D Object Detection Model without 3D Data—0
TrajSSL: Trajectory-Enhanced Semi-Supervised 3D Object Detection—0
TransCAR: Transformer-based Camera-And-Radar Fusion for 3D Object Detection—0
Transferable Semi-supervised 3D Object Detection from RGB-D Data—0
Transfer Learning from Simulated to Real Scenes for Monocular 3D Object Detection—0
Transformation-Equivariant 3D Object Detection for Autonomous Driving—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