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

Showing 251300 of 1576 papers

TitleStatusHype
Point Cloud Self-supervised Learning via 3D to Multi-view Masked AutoencoderCode1
Flow-Based Feature Fusion for Vehicle-Infrastructure Cooperative 3D Object DetectionCode1
HEDNet: A Hierarchical Encoder-Decoder Network for 3D Object Detection in Point CloudsCode1
GUPNet++: Geometry Uncertainty Propagation Network for Monocular 3D Object DetectionCode1
EarlyBird: Early-Fusion for Multi-View Tracking in the Bird's Eye ViewCode1
Towards Generalizable Multi-Camera 3D Object Detection via Perspective DebiasingCode1
MonoSKD: General Distillation Framework for Monocular 3D Object Detection via Spearman Correlation CoefficientCode1
Open-CRB: Towards Open World Active Learning for 3D Object DetectionCode1
Dual Radar: A Multi-modal Dataset with Dual 4D Radar for Autonomous DrivingCode1
Uni3DETR: Unified 3D Detection TransformerCode1
WLST: Weak Labels Guided Self-training for Weakly-supervised Domain Adaptation on 3D Object DetectionCode1
CoBEV: Elevating Roadside 3D Object Detection with Depth and Height ComplementarityCode1
Robust 3D Object Detection from LiDAR-Radar Point Clouds via Cross-Modal Feature AugmentationCode1
DistillBEV: Boosting Multi-Camera 3D Object Detection with Cross-Modal Knowledge DistillationCode1
UniBEV: Multi-modal 3D Object Detection with Uniform BEV Encoders for Robustness against Missing Sensor ModalitiesCode1
Robust 6DoF Pose Estimation Against Depth Noise and a Comprehensive Evaluation on a Mobile DatasetCode1
Towards Robust Robot 3D Perception in Urban Environments: The UT Campus Object DatasetCode1
MonoUNI: A Unified Vehicle and Infrastructure-side Monocular 3D Object Detection Network with Sufficient Depth CluesCode1
FGFusion: Fine-Grained Lidar-Camera Fusion for 3D Object DetectionCode1
SupFusion: Supervised LiDAR-Camera Fusion for 3D Object DetectionCode1
SOGDet: Semantic-Occupancy Guided Multi-view 3D Object DetectionCode1
Delving into Motion-Aware Matching for Monocular 3D Object TrackingCode1
UniM^2AE: Multi-modal Masked Autoencoders with Unified 3D Representation for 3D Perception in Autonomous DrivingCode1
DatasetEquity: Are All Samples Created Equal? In The Quest For Equity Within DatasetsCode1
MonoNeRD: NeRF-like Representations for Monocular 3D Object DetectionCode1
Far3D: Expanding the Horizon for Surround-view 3D Object DetectionCode1
ImGeoNet: Image-induced Geometry-aware Voxel Representation for Multi-view 3D Object DetectionCode1
GPA-3D: Geometry-aware Prototype Alignment for Unsupervised Domain Adaptive 3D Object Detection from Point CloudsCode1
MS3D++: Ensemble of Experts for Multi-Source Unsupervised Domain Adaption in 3D Object DetectionCode1
V-DETR: DETR with Vertex Relative Position Encoding for 3D Object DetectionCode1
PARTNER: Level up the Polar Representation for LiDAR 3D Object DetectionCode1
Spatio-Temporal Domain Awareness for Multi-Agent Collaborative PerceptionCode1
PG-RCNN: Semantic Surface Point Generation for 3D Object DetectionCode1
HVDetFusion: A Simple and Robust Camera-Radar Fusion FrameworkCode1
CORE: Cooperative Reconstruction for Multi-Agent PerceptionCode1
SA-BEV: Generating Semantic-Aware Bird's-Eye-View Feature for Multi-view 3D Object DetectionCode1
RCM-Fusion: Radar-Camera Multi-Level Fusion for 3D Object DetectionCode1
Revisiting Domain-Adaptive 3D Object Detection by Reliable, Diverse and Class-balanced Pseudo-LabelingCode1
Practical Collaborative Perception: A Framework for Asynchronous and Multi-Agent 3D Object DetectionCode1
Spatial-Temporal Graph Enhanced DETR Towards Multi-Frame 3D Object DetectionCode1
Tame a Wild Camera: In-the-Wild Monocular Camera CalibrationCode1
Predict to Detect: Prediction-guided 3D Object Detection using Sequential ImagesCode1
MoDAR: Using Motion Forecasting for 3D Object Detection in Point Cloud SequencesCode1
Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastCode1
Radar Enlighten the Dark: Enhancing Low-Visibility Perception for Automated Vehicles with Camera-Radar FusionCode1
Learning Occupancy for Monocular 3D Object DetectionCode1
Bridging the Domain Gap: Self-Supervised 3D Scene Understanding with Foundation ModelsCode1
SSD-MonoDETR: Supervised Scale-aware Deformable Transformer for Monocular 3D Object DetectionCode1
Multi-Modal 3D Object Detection by Box MatchingCode1
3D Small Object Detection with Dynamic Spatial PruningCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1EA-LSSNDS0.78Unverified
2MMFusion-eNDS0.77Unverified
3MegFusionNDS0.77Unverified
4RacoonPowerNDS0.76Unverified
5BEVFusion-eNDS0.76Unverified
6DeepInteraction-largeNDS0.76Unverified
7DeepInteraction-eNDS0.76Unverified
8DAANDS0.75Unverified
9FusionVPENDS0.75Unverified
10CenterPoint-FusionNDS0.75Unverified