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 1311–1320 of 1576 papers

TitleStatusHype
PAI3D: Painting Adaptive Instance-Prior for 3D Object Detection—0
PALF: Pre-Annotation and Camera-LiDAR Late Fusion for the Easy Annotation of Point Clouds—0
PandaSet: Advanced Sensor Suite Dataset for Autonomous Driving—0
PanoContext-Former: Panoramic Total Scene Understanding with a Transformer—0
Panopticus: Omnidirectional 3D Object Detection on Resource-constrained Edge Devices—0
PatchContrast: Self-Supervised Pre-training for 3D Object Detection—0
Patch Refinement -- Localized 3D Object Detection—0
Pattern-Aware Data Augmentation for LiDAR 3D Object Detection—0
PC-RGNN: Point Cloud Completion and Graph Neural Network for 3D Object Detection—0
PerspectiveNet: 3D Object Detection from a Single RGB Image via Perspective Points—0
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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