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 131–140 of 1576 papers

TitleStatusHype
Real-Time 3D Object Detection Using InnovizOne LiDAR and Low-Power Hailo-8 AI AcceleratorCode0
Towards Flexible 3D Perception: Object-Centric Occupancy Completion Augments 3D Object DetectionCode1
Cubify Anything: Scaling Indoor 3D Object DetectionCode3
Reflective Teacher: Semi-Supervised Multimodal 3D Object Detection in Bird's-Eye-View via Uncertainty Measure—0
TREND: Unsupervised 3D Representation Learning via Temporal Forecasting for LiDAR Perception—0
Redundant Queries in DETR-Based 3D Detection Methods: Unnecessary and PrunableCode0
MCBLT: Multi-Camera Multi-Object 3D Tracking in Long Videos—0
Bootstraping Clustering of Gaussians for View-consistent 3D Scene UnderstandingCode1
SpaRC: Sparse Radar-Camera Fusion for 3D Object DetectionCode0
OpenAD: Open-World Autonomous Driving Benchmark for 3D Object DetectionCode2
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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