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.

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Papers

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Showing 301–350 of 1576 papers

TitleStatusHype
GrooMeD-NMS: Grouped Mathematically Differentiable NMS for Monocular 3D Object DetectionCode1
GPA-3D: Geometry-aware Prototype Alignment for Unsupervised Domain Adaptive 3D Object Detection from Point CloudsCode1
Ground-aware Monocular 3D Object Detection for Autonomous DrivingCode1
Harnessing Uncertainty-aware Bounding Boxes for Unsupervised 3D Object DetectionCode1
Holistic 3D Scene Understanding from a Single Image with Implicit RepresentationCode1
Kinematic 3D Object Detection in Monocular VideoCode1
Learning to Detect Objects from Multi-Agent LiDAR Scans without Manual LabelsCode1
Curricular Object Manipulation in LiDAR-based Object DetectionCode1
GeoBEV: Learning Geometric BEV Representation for Multi-view 3D Object DetectionCode1
Geometry-based Distance Decomposition for Monocular 3D Object DetectionCode1
AYDIV: Adaptable Yielding 3D Object Detection via Integrated Contextual Vision TransformerCode1
CubeSLAM: Monocular 3D Object SLAMCode1
FusionPainting: Multimodal Fusion with Adaptive Attention for 3D Object DetectionCode1
General Geometry-aware Weakly Supervised 3D Object DetectionCode1
Geometry Uncertainty Projection Network for Monocular 3D Object DetectionCode1
CRT-Fusion: Camera, Radar, Temporal Fusion Using Motion Information for 3D Object DetectionCode1
3D Object Detection from Images for Autonomous Driving: A SurveyCode1
Back to Reality: Weakly-supervised 3D Object Detection with Shape-guided Label EnhancementCode1
Cross-Modality Knowledge Distillation Network for Monocular 3D Object DetectionCode1
Depth-conditioned Dynamic Message Propagation for Monocular 3D Object DetectionCode1
Back-tracing Representative Points for Voting-based 3D Object Detection in Point CloudsCode1
Graph R-CNN: Towards Accurate 3D Object Detection with Semantic-Decorated Local GraphCode1
Group-Free 3D Object Detection via TransformersCode1
GSPN: Generative Shape Proposal Network for 3D Instance Segmentation in Point CloudCode1
Fully Sparse Fusion for 3D Object DetectionCode1
Fusing Event-based and RGB camera for Robust Object Detection in Adverse ConditionsCode1
Frustum-PointPillars: A Multi-Stage Approach for 3D Object Detection using RGB Camera and LiDARCode1
DatasetEquity: Are All Samples Created Equal? In The Quest For Equity Within DatasetsCode1
DBQ-SSD: Dynamic Ball Query for Efficient 3D Object DetectionCode1
DCDet: Dynamic Cross-based 3D Object DetectorCode1
A Comprehensive Study of the Robustness for LiDAR-based 3D Object Detectors against Adversarial AttacksCode1
Benchmarking Robustness of 3D Object Detection to Common CorruptionsCode1
Benchmarking the Robustness of LiDAR-Camera Fusion for 3D Object DetectionCode1
FSD-BEV: Foreground Self-Distillation for Multi-view 3D Object DetectionCode1
CrossDTR: Cross-view and Depth-guided Transformers for 3D Object DetectionCode1
AD-L-JEPA: Self-Supervised Spatial World Models with Joint Embedding Predictive Architecture for Autonomous Driving with LiDAR DataCode1
AutoShape: Real-Time Shape-Aware Monocular 3D Object DetectionCode1
HoughNet: Integrating near and long-range evidence for visual detectionCode1
Densely Constrained Depth Estimator for Monocular 3D Object DetectionCode1
Fusion is Not Enough: Single Modal Attacks on Fusion Models for 3D Object DetectionCode1
GLENet: Boosting 3D Object Detectors with Generative Label Uncertainty EstimationCode1
HVPR: Hybrid Voxel-Point Representation for Single-stage 3D Object DetectionCode1
CRN: Camera Radar Net for Accurate, Robust, Efficient 3D PerceptionCode1
From Multi-View to Hollow-3D: Hallucinated Hollow-3D R-CNN for 3D Object DetectionCode1
Fog Simulation on Real LiDAR Point Clouds for 3D Object Detection in Adverse WeatherCode1
Improving 3D Object Detection with Channel-wise TransformerCode1
Deep Learning for 3D Point Clouds: A SurveyCode1
BEVDistill: Cross-Modal BEV Distillation for Multi-View 3D Object DetectionCode1
A Comprehensive Review of 3D Object Detection in Autonomous Driving: Technological Advances and Future DirectionsCode1
Fooling LiDAR Perception via Adversarial Trajectory PerturbationCode1
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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