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20232026
most citedText2CAD: Text to 3D CAD Generation via Technical Drawings

4 citations · 4 across the 4 of their papers we have counts for

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5 papers · 1 filter

cs.CV2026

PrintAnything: Learning an Intermediate Representation for 3D printing G-code Generation

Sangmin Hong, Daniel Sungho Jung, Heewon Kim +1

Point clouds are one of the most fundamental and widely used 3D representations, serving as the most basic geometric representation of 3D shapes. Nevertheless, most existing 3D pri…

cs.CV2025

StarryGazer: Leveraging Monocular Depth Estimation Models for Domain-Agnostic Single Depth Image Completion

Sangmin Hong, Suyoung Lee, Kyoung Mu Lee

The problem of depth completion involves predicting a dense depth image from a single sparse depth map and an RGB image. Unsupervised depth completion methods have been proposed fo…

cs.CV2024★ 4 cited

Text2CAD: Text to 3D CAD Generation via Technical Drawings

Mohsen Yavartanoo, Sangmin Hong, Reyhaneh Neshatavar +1

The generation of industrial Computer-Aided Design (CAD) models from user requests and specifications is crucial to enhancing efficiency in modern manufacturing. Traditional method…

cs.CV2023

CNC-Net: Self-Supervised Learning for CNC Machining Operations

Mohsen Yavartanoo, Sangmin Hong, Reyhaneh Neshatavar +1

CNC manufacturing is a process that employs computer numerical control (CNC) machines to govern the movements of various industrial tools and machinery, encompassing equipment rang…

cs.CV2023

ACL-SPC: Adaptive Closed-Loop system for Self-Supervised Point Cloud Completion

Sangmin Hong, Mohsen Yavartanoo, Reyhaneh Neshatavar +1

Point cloud completion addresses filling in the missing parts of a partial point cloud obtained from depth sensors and generating a complete point cloud. Although there has been st…