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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1501–1525 of 1576 papers

TitleStatusHype
Monocular 3D Object Detection via Geometric Reasoning on Keypoints—0
Cooper: Cooperative Perception for Connected Autonomous Vehicles based on 3D Point Clouds—0
Deep Fitting Degree Scoring Network for Monocular 3D Object Detection—0
Sensor Fusion for Joint 3D Object Detection and Semantic Segmentation—0
Transferable Semi-supervised 3D Object Detection from RGB-D Data—0
DirectShape: Direct Photometric Alignment of Shape Priors for Visual Vehicle Pose and Shape Estimation—0
Deep Optics for Monocular Depth Estimation and 3D Object Detection—0
3D Object Recognition with Ensemble Learning --- A Study of Point Cloud-Based Deep Learning ModelsCode0
Complexer-YOLO: Real-Time 3D Object Detection and Tracking on Semantic Point Clouds—0
Monocular 3D Object Detection Leveraging Accurate Proposals and Shape ReconstructionCode0
MVX-Net: Multimodal VoxelNet for 3D Object Detection—0
Learning 2D to 3D Lifting for Object Detection in 3D for Autonomous Vehicles—0
Accurate Monocular Object Detection via Color-Embedded 3D Reconstruction for Autonomous Driving—0
FVNet: 3D Front-View Proposal Generation for Real-Time Object Detection from Point Clouds—0
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
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
Show:102550
← PrevPage 61 of 64Next →
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