Yizhak Ben-Shabat

Orcid: 0000-0001-7547-7493

According to our database1, Yizhak Ben-Shabat authored at least 18 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
IKEA Ego 3D Dataset: Understanding furniture assembly actions from ego-view 3D Point Clouds.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

2023
PatchContrast: Self-Supervised Pre-training for 3D Object Detection.
CoRR, 2023

3DInAction: Understanding Human Actions in 3D Point Clouds.
CoRR, 2023

Aligning Step-by-Step Instructional Diagrams to Video Demonstrations.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

GraVoS: Voxel Selection for 3D Point-Cloud Detection.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Octree Guided Unoriented Surface Reconstruction.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
GraVoS: Gradient based Voxel Selection for 3D Detection.
CoRR, 2022

CloudWalker: Random walks for 3D point cloud shape analysis.
Comput. Graph., 2022

GoferBot: A Visual Guided Human-Robot Collaborative Assembly System.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

DiGS : Divergence guided shape implicit neural representation for unoriented point clouds.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
CloudWalker: 3D Point Cloud Learning by Random Walks for Shape Analysis.
CoRR, 2021

The IKEA ASM Dataset: Understanding People Assembling Furniture through Actions, Objects and Pose.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

2020
DPDist: Comparing Point Clouds Using Deep Point Cloud Distance.
Proceedings of the Computer Vision - ECCV 2020, 2020

DeepFit: 3D Surface Fitting via Neural Network Weighted Least Squares.
Proceedings of the Computer Vision - ECCV 2020, 2020

2019
Nesti-Net: Normal Estimation for Unstructured 3D Point Clouds Using Convolutional Neural Networks.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018
3DmFV: Three-Dimensional Point Cloud Classification in Real-Time Using Convolutional Neural Networks.
IEEE Robotics Autom. Lett., 2018

Graph based over-segmentation methods for 3D point clouds.
Comput. Vis. Image Underst., 2018

2017
3D Point Cloud Classification and Segmentation using 3D Modified Fisher Vector Representation for Convolutional Neural Networks.
CoRR, 2017


  Loading...