Computer Vision Lab

Warsaw University of Technology

Computer Vision Lab is a research group at Warsaw University of Technology that gathers faculty and students working together on topics at the intersection of computer vision, machine learning and perception.

Group members

Faculty

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Kamil Deja

Assistant Professor

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Jacek Komorowski

Assistant Professor

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Mateusz Ostaszewski

Assistant Professor

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Tomasz Trzciński

Principal Investigator

PhD Students

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Michał Bortkiewicz

PhD Student

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Konrad Cop

PhD Student

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Jan Dubiński

PhD Student

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Kacper Kania

PhD Student

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Daniel Marczak

PhD Student

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Wojciech Masarczyk

PhD Student

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Stanisław Pawlak

PhD Student

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Filip Szatkowski

PhD Student

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Monika Wysoczańska

PhD Student

Publications

Towards More Realistic Membership Inference Attacks on Large Diffusion Models

January 2024 WACV 2024
Generative diffusion models, including Stable Diffusion and Midjourney, can generate visually appealing, diverse, and high-resolution …
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Towards More Realistic Membership Inference Attacks on Large Diffusion Models

Bucks for Buckets (B4B): Active Defenses Against Stealing Encoders

December 2023 NeurIPS 2023
Machine Learning as a Service (MLaaS) APIs provide ready-to-use and high-utility encoders that generate vector representations for …
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Bucks for Buckets (B4B): Active Defenses Against Stealing Encoders

BlendFields: Few-Shot Example-Driven Facial Modeling

June 2023 CVPR 2023
Generating faithful visualizations of human faces requires capturing both coarse and fine-level details of the face geometry and …
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BlendFields: Few-Shot Example-Driven Facial Modeling

Learning Data Representations with Joint Diffusion Models

April 2023 ECML 2023
Joint machine learning models that allow synthesizing and classifying data often offer uneven performance between those tasks or are …
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Learning Data Representations with Joint Diffusion Models

On Analyzing Generative and Denoising Capabilities of Diffusion-based Deep Generative Models

December 2022 NeurIPS 2022
Diffusion-based Deep Generative Models (DDGMs) offer state-of-the-art performance in generative modeling. Their main strength comes …
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On Analyzing Generative and Denoising Capabilities of Diffusion-based Deep Generative Models
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Funded Projects

Continual Self-Supervised Representation Learning - Grant PRELUDIUM BIS funded by National Science Centre Poland

We tackle the problem of learning representations in continual learning regime.
Continual Self-Supervised Representation Learning - Grant PRELUDIUM BIS funded by National Science Centre Poland

OPUS funding from National Science Centre in Poland

Application of deep generative models for lifelong learning.
OPUS funding from National Science Centre in Poland

Microsoft Research PhD Scholarship Award

Low shot realistic human rendering from partial information.
Microsoft Research PhD Scholarship Award

Grant of Priority Research Domain at WUT - Artificial Intelligence and Robotics

Binary representations and their application in continual learning.
Grant of Priority Research Domain at WUT - Artificial Intelligence and Robotics

Grant of Priority Research Domain at WUT - High Energy Physics and Experimental Techniques

WUT@ALICE: Study of fundamental properties of strongly interacting matter with particle correlations and machine learning in ALICE at LHC.
Grant of Priority Research Domain at WUT - High Energy Physics and Experimental Techniques
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Open positions

Prospective Grad Students

Master Oct 2020
We are always looking for highly motivated and talented students. Take a look at this url to find out more.

Prospective PhD Students

PhD Oct 2020
We are always looking for highly motivated and talented students. PhD admissions at WUT are centralized and if you are seeking a PhD position, please apply to the Doctoral School no. 3 at Warsaw University of Technology.

Prospective Postdocs

PostDoc Oct 2020
Please contact us directly with your resume.

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