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 901–925 of 1576 papers

TitleStatusHype
Sample, Crop, Track: Self-Supervised Mobile 3D Object Detection for Urban Driving LiDAR—0
Self-supervised 3D Object Detection from Monocular Pseudo-LiDAR—0
Rethinking Dimensionality Reduction in Grid-based 3D Object Detection—0
LidarMultiNet: Towards a Unified Multi-Task Network for LiDAR Perception—0
A Dual-Cycled Cross-View Transformer Network for Unified Road Layout Estimation and 3D Object Detection in the Bird's-Eye-ViewCode1
FFPA-Net: Efficient Feature Fusion with Projection Awareness for 3D Object Detection—0
Viewer-Centred Surface Completion for Unsupervised Domain Adaptation in 3D Object DetectionCode1
CRAFT: Camera-Radar 3D Object Detection with Spatio-Contextual Fusion Transformer—0
CMR3D: Contextualized Multi-Stage Refinement for 3D Object Detection—0
CenterFormer: Center-based Transformer for 3D Object DetectionCode2
Multi-modal Streaming 3D Object Detection—0
MSMDFusion: Fusing LiDAR and Camera at Multiple Scales with Multi-Depth Seeds for 3D Object DetectionCode0
SEFormer: Structure Embedding Transformer for 3D Object Detection—0
Scatter Points in Space: 3D Detection from Multi-view Monocular Images—0
3DLG-Detector: 3D Object Detection via Simultaneous Local-Global Feature Learning—0
PV-RCNN++: Semantical Point-Voxel Feature Interaction for 3D Object Detection—0
Bridging the View Disparity Between Radar and Camera Features for Multi-modal Fusion 3D Object Detection—0
Anytime-Lidar: Deadline-aware 3D Object Detection—0
AGO-Net: Association-Guided 3D Point Cloud Object Detection Network—0
DeepInteraction: 3D Object Detection via Modality InteractionCode2
Quality Matters: Embracing Quality Clues for Robust 3D Multi-Object Tracking—0
Minkowski Tracker: A Sparse Spatio-Temporal R-CNN for Joint Object Detection and Tracking—0
STS: Surround-view Temporal Stereo for Multi-view 3D Detection—0
A Simple Baseline for Multi-Camera 3D Object DetectionCode1
MonoSIM: Simulating Learning Behaviors of Heterogeneous Point Cloud Object Detectors for Monocular 3D Object DetectionCode0
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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