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
The Why, When, and How to Use Active Learning in Large-Data-Driven 3D Object Detection for Safe Autonomous Driving: An Empirical Exploration—0
Three-Dimensional Object Detection and Layout Prediction Using Clouds of Oriented Gradients—0
TICaM: A Time-of-flight In-car Cabin Monitoring Dataset—0
Time3D: End-to-End Joint Monocular 3D Object Detection and Tracking for Autonomous Driving—0
Time-to-Label: Temporal Consistency for Self-Supervised Monocular 3D Object Detection—0
To the Point: Efficient 3D Object Detection in the Range Image with Graph Convolution Kernels—0
Toward Accurate Camera-based 3D Object Detection via Cascade Depth Estimation and Calibration—0
Towards 3D Object Detection with 2D Supervision—0
Towards 3D Object Detection With Bimodal Deep Boltzmann Machines Over RGBD Imagery—0
Towards Autonomous Driving: a Multi-Modal 360^ Perception Proposal—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