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 1391–1400 of 1576 papers

TitleStatusHype
PV-RCNN: The Top-Performing LiDAR-only Solutions for 3D Detection / 3D Tracking / Domain Adaptation of Waymo Open Dataset Challenges—0
3D for Free: Crossmodal Transfer Learning using HD Maps—0
Towards Autonomous Driving: a Multi-Modal 360^ Perception Proposal—0
Cross-Modality 3D Object Detection—0
Multi-Class 3D Object Detection Within Volumetric 3D Computed Tomography Baggage Security Screening Imagery—0
Distance-Normalized Unified Representation for Monocular 3D Object Detection—0
Rotation-robust Intersection over Union for 3D Object Detection—0
Monocular 3D Object Detection via Feature Domain Adaptation—0
An LSTM Approach to Temporal 3D Object Detection in LiDAR Point Clouds—0
Object-Aware Centroid Voting for Monocular 3D Object Detection—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1EA-LSSNDS0.78—Unverified
2MegFusionNDS0.77—Unverified
3MMFusion-eNDS0.77—Unverified
4BEVFusion-eNDS0.76—Unverified
5RacoonPowerNDS0.76—Unverified
6DeepInteraction-largeNDS0.76—Unverified
7DeepInteraction-eNDS0.76—Unverified
8FusionVPENDS0.75—Unverified
9FocalFormer3D-FNDS0.75—Unverified
10CenterPoint-FusionNDS0.75—Unverified