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 326–350 of 1576 papers

TitleStatusHype
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