Name: | Ziya Erkoc |
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Position: | Ph.D Candidate |
E-Mail: | ziya.erkoc@tum.de |
Phone: | TBD |
Room No: | 02.07.041 |
Hi, my name is Ziya. I received my BSc and MSc in Computer Engineering degrees from Bilkent University, Turkey. I've previously worked on memory-efficient tetrahedral mesh generation. During my bachelor's years, I participated in Google Summer of Code as a contributor to the cBioPortal for Cancer Genomics tool. In addition, I worked at Taleworlds Entertainment as a software engineering intern. Homepage
PrEditor3D: Fast and Precise 3D Shape Editing |
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Ziya Erkoç, Can Gümeli, Chaoyang Wang, Matthias Nießner, Angela Dai, Peter Wonka, Hsin-Ying Lee, Peiye Zhuang |
CVPR 2025 |
We propose a training-free approach to 3D editing that enables the editing of a single shape within a few minutes. The edited 3D mesh aligns well with the prompts, and remains identical for regions that are not intended to be altered. Extensive experiments demonstrate the superiority of our method over previous approaches, enabling fast, high-quality editing while preserving unintended regions. |
[video][bibtex][project page] |
HyperDiffusion: Generating Implicit Neural Fields with Weight-Space Diffusion |
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Ziya Erkoç, Fangchang Ma, Qi Shan, Matthias Nießner, Angela Dai |
ICCV 2023 |
We propose HyperDiffusion, a novel approach for unconditional generative modeling of implicit neural fields. HyperDiffusion operates directly on MLP weights and generates new neural implicit fields encoded by synthesized MLP parameters. It enables diffusion modeling over a implicit, compact, and yet high-fidelity representation of complex signals across 3D shapes and 4D mesh animations within one single unified framework. |
[video][bibtex][project page] |