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 1501–1550 of 1576 papers

TitleStatusHype
GS3D: An Efficient 3D Object Detection Framework for Autonomous Driving—0
Monocular 3D Object Detection with Pseudo-LiDAR Point CloudCode0
LaserNet: An Efficient Probabilistic 3D Object Detector for Autonomous Driving—0
Frustum ConvNet: Sliding Frustums to Aggregate Local Point-Wise Features for Amodal 3D Object DetectionCode0
The H3D Dataset for Full-Surround 3D Multi-Object Detection and Tracking in Crowded Urban Scenes—0
DPOD: 6D Pose Object Detector and RefinerCode0
Stereo R-CNN based 3D Object Detection for Autonomous DrivingCode0
PIXOR: Real-time 3D Object Detection from Point CloudsCode1
Real-time 3D Traffic Cone Detection for Autonomous DrivingCode0
Three-dimensional Backbone Network for 3D Object Detection in Traffic ScenesCode0
DenseFusion: 6D Object Pose Estimation by Iterative Dense FusionCode0
3D Object Detection Using Scale Invariant and Feature Reweighting Networks—0
Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous DrivingCode1
3D-SIS: 3D Semantic Instance Segmentation of RGB-D ScansCode0
PointPillars: Fast Encoders for Object Detection from Point CloudsCode2
IPOD: Intensive Point-based Object Detector for Point Cloud—0
PointRCNN: 3D Object Proposal Generation and Detection from Point CloudCode1
GSPN: Generative Shape Proposal Network for 3D Instance Segmentation in Point CloudCode1
ROI-10D: Monocular Lifting of 2D Detection to 6D Pose and Metric Shape—0
Explaining the Ambiguity of Object Detection and 6D Pose From Visual Data—0
Joint Monocular 3D Vehicle Detection and TrackingCode0
MonoGRNet: A Geometric Reasoning Network for Monocular 3D Object LocalizationCode0
Orthographic Feature Transform for Monocular 3D Object DetectionCode0
RoarNet: A Robust 3D Object Detection based on RegiOn Approximation Refinement—0
Cooperative Holistic Scene Understanding: Unifying 3D Object, Layout, and Camera Pose EstimationCode0
SECOND: Sparsely Embedded Convolutional DetectionCode2
Focal Loss in 3D Object DetectionCode0
Eliminating the Blind Spot: Adapting 3D Object Detection and Monocular Depth Estimation to 360° Panoramic Imagery—0
Eliminating the Blind Spot: Adapting 3D Object Detection and Monocular Depth Estimation to 360° Panoramic ImageryCode0
Holistic 3D Scene Parsing and Reconstruction from a Single RGB ImageCode0
PointSeg: Real-Time Semantic Segmentation Based on 3D LiDAR Point CloudCode0
Leveraging Pre-Trained 3D Object Detection Models For Fast Ground Truth Generation—0
Symmetry Aware Evaluation of 3D Object Detection and Pose Estimation in Scenes of Many Parts in Bulk—0
Multi-Level Fusion Based 3D Object Detection From Monocular Images—0
3D Object Detection With Latent Support Surfaces—0
CubeSLAM: Monocular 3D Object SLAMCode1
Scene Understanding Networks for Autonomous Driving based on Around View Monitoring System—0
BirdNet: a 3D Object Detection Framework from LiDAR informationCode1
Falling Things: A Synthetic Dataset for 3D Object Detection and Pose Estimation—0
Complex-YOLO: Real-time 3D Object Detection on Point CloudsCode2
A General Pipeline for 3D Detection of Vehicles—0
SBNet: Sparse Blocks Network for Fast InferenceCode0
Joint 3D Proposal Generation and Object Detection from View AggregationCode0
PointFusion: Deep Sensor Fusion for 3D Bounding Box EstimationCode0
SGPN: Similarity Group Proposal Network for 3D Point Cloud Instance SegmentationCode0
Frustum PointNets for 3D Object Detection from RGB-D DataCode1
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object DetectionCode1
Fusing Bird View LIDAR Point Cloud and Front View Camera Image for Deep Object Detection—0
3D-SSD: Learning Hierarchical Features from RGB-D Images for Amodal 3D Object Detection—0
2D-Driven 3D Object Detection in RGB-D Images—0
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All datasetsnuScenesScanNetV2SUN-RGBD valKITTI Cars EasyKITTI Cars HardnuScenes Camera OnlyKITTI Cars Easy valKITTI Cars Moderate valnuscenes Camera-RadarView-of-Delft (val)KITTI Cars Hard valDAIR-V2X-I

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