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 1476–1500 of 1576 papers

TitleStatusHype
Learning from Unlabelled Videos Using Contrastive Predictive Neural 3D MappingCode0
Triangulation Learning Network: from Monocular to Stereo 3D Object DetectionCode0
Disentangling Monocular 3D Object Detection—0
Shift R-CNN: Deep Monocular 3D Object Detection with Closed-Form Geometric Constraints—0
RIU-Net: Embarrassingly simple semantic segmentation of 3D LiDAR point cloud—0
Multimodal 3D Object Detection from Simulated PretrainingCode0
Monocular Plan View Networks for Autonomous Driving—0
Monocular 3D Object Detection via Geometric Reasoning on Keypoints—0
Cooper: Cooperative Perception for Connected Autonomous Vehicles based on 3D Point Clouds—0
Precise Synthetic Image and LiDAR (PreSIL) Dataset for Autonomous Vehicle PerceptionCode1
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 Hough Voting for 3D Object Detection in Point CloudsCode1
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
Objects as PointsCode2
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
nuScenes: A multimodal dataset for autonomous drivingCode2
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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