Mohamad Shahbazi profile picture

Mohamad Shahbazi

Machine Learning Engineer at Apple
Zurich, Switzerland

Scholar LinkedIn GitHub

About Me

I am a Machine Learning engineer at Apple Zurich, working on various topics in Machine Learning and Computer Vision. Currently, I am focused on 3D Generative Models and Neural Rendering for Digital Humans.

Previously, I received my PhD in 2D and 3D Generative Models at the Computer Vision Lab (CVL) at ETH Zurich under the supervision of Prof. Luc Van Gool.

Research Interests

Here are some areas I am actively exploring:

Machine Learning Computer Vision Generative Models Neural Rendering Vision-Language Models Digital Humans

Experience

Machine Learning Engineer at Apple Switzerland 08/2024 - Current

Working on Digital Humans using Machine Learning and Computer Vision.

Applied Science Intern at Microsoft UK 01/2024 - 06/2024

Research internship on location modeling for object placement in images using vision-language models.

Research Intern at Google Switzerland 06/2023 - 09/2023

Research internship on 3D editing of scenes using Diffusion Models and Neural Radiance Fields.

Publications

InseRF: Text-Driven Generative Object Insertion in Neural 3D Scenes

M. Shahbazi, L. Claessens, M. Niemeyer, E. Collins, A. Tonioni, L. Van Gool, F. Tombari

ArXiv 2024
Paper Project Page

Taming the Tail in Class-Conditional GANs: Knowledge Sharing via Unconditional Training at Lower Resolutions

S. Khorram, M. Jiang, M. Shahbazi, MH. Danesh, L. Fuxin

CVPR 2024
Paper Code

StyleGenes: Discrete and Efficient Latent Distributions for GANs

E. Ntavelis, M. Shahbazi, I. Kastanis, M. Danelljan, L. Van Gool

WACV 2024
Paper

NeRF-GAN Distillation for Efficient 3D-Aware Generation with Convolutions

M. Shahbazi, E. Ntavelis, A. Tonioni, E. Collins, D. P. Paudel, M. Danelljan, L. Van Gool

ICCVW 2023
Paper Code

Diffdreamer: Towards Consistent Unsupervised Single-View Scene Extrapolation with Conditional Diffusion Models

S. Cai, E. R. Chan, S. Peng, M. Shahbazi, A. Obukhov, L. Van Gool, G. Wetzstein

ICCV 2023
Paper Project Page Code

A Continual Deepfake Detection Benchmark: Dataset, Methods, and Essentials

C. Li, Z. Huang, D. P. Paudel, Y. Wang, M. Shahbazi, X. Hong, L. Van Gool

WACV 2023
Paper Code

Training Dynamics Aware Neural Network Optimization with Stabilization

Z. Fang, M. Shahbazi, T. Probst, D. P. Paudel, L. Van Gool

ACCV 2023
Paper Code

Arbitrary-Scale Image Synthesis

E. Ntavelis, M. Shahbazi, I. Kastanis, R. Timofte, M. Danelljan, L. Van Gool

CVPR 2022
Paper Code

Collapse by Conditioning: Training Class-Conditional GANs with Limited Data

M. Shahbazi, M. Danelljan, D. P. Paudel, L. Van Gool

ICLR 2022
Paper Code

Efficient Conditional GAN Transfer with Knowledge Propagation across Classes

M. Shahbazi, Z. Huang, D. P. Paudel, A. Chhatkuli, L. Van Gool

CVPR 2021
Paper Code

A Generalizable Model for Seizure Prediction using CNN-LSTM Architecture

M. Shahbazi, H. Aghajan

IEEE GlobalSIP 2018
Paper