Stanislav Frolov

Hi, I'm a 4th year Ph.D. student at RPTU Kaiserslautern and German Research Center for Artificial Intelligence, advised by Andreas Dengel.

My main interests are computer vision and machine learning. I use deep generative models for controlled image synthesis.

In 2021, I interned at Adobe Research working with Kushal Kafle, Scott Cohen and Tobias Hinz on image editing. In 2022, I interned at Meta AI working with Adriana Romero-Soriano, Michał Drożdżal and Jakob Verbeek on spherical image generation.

Previously, I've worked at inovex as a data engineer, and completed my B.Sc. and M.Sc degrees in Electrical Engineering at the Karlsruhe Institute of Technology.

If you are interested in similar topics, want to chat or collaborate, feel free to contact me.

Email  /  Google Scholar  /  LinkedIn  /  GitHub  /  Twitter

profile photo
Research Internships
Meta 2022
Paris
Adobe 2021
Remote
News
Publications
Federated Learning for Blind Image Super-Resolution
Brian B. Moser, Ahmed Anwar, Federico Raue, Stanislav Frolov, Andreas Dengel
arXiv, 2024
ObjBlur: A Curriculum Learning Approach with Progressive Object-Level Blurring for Improved Layout-to-Image Generation
Stanislav Frolov, Brian B. Moser, Sebastian Palacio, Andreas Dengel
arXiv, 2024
Latent Dataset Distillation with Diffusion Models
Brian B. Moser, Federico Raue, Sebastian Palacio, Stanislav Frolov, Andreas Dengel
arXiv, 2024
Diffusion Models, Image Super-Resolution And Everything: A Survey
Brian B. Moser, Arundhati S. Shanbhag, Federico Raue, Stanislav Frolov, Sebastian Palacio, Andreas Dengel
arXiv, 2024
YODA: Dynamic Attention-Guided Diffusion for Image Super-Resolution
Brian Moser*, Stanislav Frolov*, Federico Raue, Sebastian Palacio, Andreas Dengel
arXiv, 2023
DWA: Differential Wavelet Amplifier for Image Super-Resolution
Brian Moser, Stanislav Frolov, Federico Raue, Sebastian Palacio, Andreas Dengel
ICANN, 2023
Are Visual Recognition Models Robust to Image Compression?
João Maria Janeiro, Stanislav Frolov, Alaaeldin El-Nouby, Jakob Verbeek
ICML Workshop on Neural Compression, 2023
Waving Goodbye to Low-Res: A Diffusion-Wavelet Approach for Image Super-Resolution
Brian Moser, Stanislav Frolov, Federico Raue, Sebastian Palacio, Andreas Dengel
IJCNN, 2024
Hitchhiker's Guide to Super-Resolution: Introduction and Recent Advances
Brian Moser, Federico Raue, Stanislav Frolov, Jörn Hees, Sebastian Palacio, Andreas Dengel
TPAMI, 2023
project page
DT2I: Dense Text-to-Image Generation from Region Descriptions
Stanislav Frolov*, Prateek Bansal*, Jörn Hees, Andreas Dengel
ICANN, 2022
Combining Transformer Generators with Convolutional Discriminators
Ricard Durall*, Stanislav Frolov*, Jörn Hees, Federico Raue, Franz-Josef Pfreundt, Andreas Dengel, Janis Keuper
GCAI, 2021
AttrLostGAN: Attribute Controlled Image Synthesis from Reconfigurable Layout and Style
Stanislav Frolov, Avneesh Sharma, Jörn Hees, Tushar Karayil, Federico Raue, Andreas Dengel
GCPR, 2021
code
Adversarial Text-to-Image Synthesis: A Review
Stanislav Frolov, Tobias Hinz, Federico Raue, Jörn Hees, Andreas Dengel
Neural Networks Journal, 2021
Hybrid-S2S: Video Object Segmentation with Recurrent Networks and Correspondence Matching
Fatemeh Azimi, Stanislav Frolov, Federico Raue, Jörn Hees, Andreas Dengel
VISIGRAPP, 2021
code
Leveraging Visual Question Answering to Improve Text-to-Image Synthesis
Stanislav Frolov, Shailza Jolly, Jörn Hees, Andreas Dengel
LANTERN workshop at COLING, 2020
slides
Reviewing
  • Conference: CVPR'23-'24, ICLR'23, NeurIPS'23, ECCV '24, WACV'21-'23, ICANN'22-'23, GCAI'21, GCPR'21, DAS'20
  • Workshop: LANTERN'21
  • Journal: APIN'21

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