collaborators

9 papers

cs.AI2026

InstructMesh: Selective Refinement of Generative 3D Models for Fabrication

Faraz Faruqi, Ahmed Katary, Demircan Tas +10

Recent advances in generative AI allow users to create 3D models from text or images. However, these models prioritize visual plausibility over geometric accuracy, often generating…

cs.HC2026

MiXR: Harvesting and Recomposing Geometry from Real-World Objects for In-Situ 3D Design

Faraz Faruqi, Demircan Tas, Arthur Caetano +6

Recent developments in 3D generative AI enable users to create bespoke 3D models from text or image prompts. However, these approaches provide limited control over spatial structur…

cs.CV2023

Embedded Shape Matching in Photogrammetry Data for Modeling Making Knowledge

Demircan Tas, Mine Özkar

In three-dimensional models obtained by photogrammetry of existing structures, all of the shapes that the eye can select cannot always find their equivalents in the geometric compo…

cs.GR2023

Design Systems for Closing Gaps with Rheotomic Surfaces and Allometry

Demircan Tas

This study aims to present a material based, second order design method that makes the rapid creation of bridging structures in order to connect two or more horizontal planes which…

cs.GR2023

Generating Forms via Informed Motion, a Flight Inspired Method Based on Wind and Topography Data

Demircan Tas, Osman Sumer

Generative systems are becoming a crucial part of current design practice. There exist gaps however, between the digital processes, field data and designer's input. To solve this p…

cs.CV2023

Unveiling Spaces: Architecturally meaningful semantic descriptions from images of interior spaces

Demircan Tas, Rohit Priyadarshi Sanatani

There has been a growing adoption of computer vision tools and technologies in architectural design workflows over the past decade. Notable use cases include point cloud generation…