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 1351–1400 of 1576 papers

TitleStatusHype
Local Grid Rendering Networks for 3D Object Detection in Point Clouds—0
Optimisation of the PointPillars network for 3D object detection in point clouds—0
Boosting Deep Neural Networks with Geometrical Prior Knowledge: A Survey—0
Expandable YOLO: 3D Object Detection from RGB-D Images—0
AFDet: Anchor Free One Stage 3D Object DetectionCode1
Single-Shot 3D Detection of Vehicles from Monocular RGB Images via Geometry Constrained Keypoints in Real-Time—0
Towards Better Performance and More Explainable Uncertainty for 3D Object Detection of Autonomous Vehicles—0
Generative Sparse Detection Networks for 3D Single-shot Object DetectionCode2
Center-based 3D Object Detection and TrackingCode2
Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies—0
H3DNet: 3D Object Detection Using Hybrid Geometric PrimitivesCode1
Stereo RGB and Deeper LIDAR Based Network for 3D Object Detection—0
Associate-3Ddet: Perceptual-to-Conceptual Association for 3D Point Cloud Object Detection—0
CubifAE-3D: Monocular Camera Space Cubification for Auto-Encoder based 3D Object Detection—0
SVGA-Net: Sparse Voxel-Graph Attention Network for 3D Object Detection from Point Clouds—0
3D-MPA: Multi-Proposal Aggregation for 3D Semantic Instance SegmentationCode1
A Hierarchical Graph Network for 3D Object Detection on Point Clouds—0
Density-Based Clustering for 3D Object Detection in Point Clouds—0
Structure Aware Single-Stage 3D Object Detection From Point CloudCode1
IDA-3D: Instance-Depth-Aware 3D Object Detection From Stereo Vision for Autonomous DrivingCode1
Single-Shot Monocular RGB-D Imaging Using Uneven Double Refraction—0
BidNet: Binocular Image Dehazing Without Explicit Disparity EstimationCode0
Joint 3D Instance Segmentation and Object Detection for Autonomous Driving—0
Center3D: Center-based Monocular 3D Object Detection with Joint Depth Understanding—0
RV-FuseNet: Range View Based Fusion of Time-Series LiDAR Data for Joint 3D Object Detection and Motion Forecasting—0
Range Conditioned Dilated Convolutions for Scale Invariant 3D Object DetectionCode1
Train in Germany, Test in The USA: Making 3D Object Detectors GeneralizeCode1
Exploring the Capabilities and Limits of 3D Monocular Object Detection -- A Study on Simulation and Real World Data—0
RUHSNet: 3D Object Detection Using Lidar Data in Real TimeCode0
View Invariant Human Body Detection and Pose Estimation from Multiple Depth Sensors—0
Drosophila-Inspired 3D Moving Object Detection Based on Point Clouds—0
SS3D: Single Shot 3D Object Detector—0
3D-CVF: Generating Joint Camera and LiDAR Features Using Cross-View Spatial Feature Fusion for 3D Object DetectionCode1
3D Object Detection Method Based on YOLO and K-Means for Image and Point Clouds—0
YOLO and K-Means Based 3D Object Detection Method on Image and Point Cloud—0
Learning to Evaluate Perception Models Using Planner-Centric Metrics—0
ALCN: Adaptive Local Contrast Normalization—0
MLCVNet: Multi-Level Context VoteNet for 3D Object DetectionCode1
Disp R-CNN: Stereo 3D Object Detection via Shape Prior Guided Instance Disparity EstimationCode1
End-to-End Pseudo-LiDAR for Image-Based 3D Object DetectionCode1
SSN: Shape Signature Networks for Multi-class Object Detection from Point CloudsCode1
Finding Your (3D) Center: 3D Object Detection Using a Learned LossCode1
Quantifying Data Augmentation for LiDAR based 3D Object Detection—0
Improving 3D Object Detection through Progressive Population Based Augmentation—0
DOPS: Learning to Detect 3D Objects and Predict their 3D Shapes—0
Boundary-Aware Dense Feature Indicator for Single-Stage 3D Object Detection from Point Clouds—0
3D-MPA: Multi Proposal Aggregation for 3D Semantic Instance SegmentationCode1
Predicting Semantic Map Representations from Images using Pyramid Occupancy NetworksCode1
On the Evaluation of Prohibited Item Classification and Detection in Volumetric 3D Computed Tomography Baggage Security Screening Imagery—0
Safety-Aware Hardening of 3D Object Detection Neural Network Systems—0
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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