2 citations · 2 across the 6 of their papers we have counts for
7 papers
CryoTracer: A Synthetic-to-Real System for Filament Instance Tracing in Cryo-EM
Radosław Kuczbański, Wojciech Kozłowski, Mateusz Grzesiuk +4
Particle picking in cryo-electron microscopy is commonly formulated as an object-detection problem in which individual particles are represented by bounding boxes, a natural repres…
DART: A Degradation-Aware Recurrent Transformer for Archival Film Restoration
Mikołaj Jastrzębski, Wojciech Kozłowski, Kamil Adamczewski
Archival film restoration is a challenging problem because historical footage contains compound degradations such as scratches, dust, blur, noise, flicker, and photometric aging, w…
AbsoluteDegradation: A Physics-Inspired Synthetic Film-Degradation Pipeline and Archival Film Restoration Benchmark
Mikołaj Jastrzębski, Dawid Glinkowski, Dawid Zieliński +3
Restoring archival film remains a fundamentally challenging problem due to the absence of paired training data and the lack of standardized evaluation benchmarks. Pristine versions…
Unifying Deep Stochastic Processes for Image Enhancement
Wojciech Kozłowski, Radosław Kuczbański, Kamil Adamczewski +2
Deep stochastic processes have recently become a central paradigm for image enhancement, with many methods explicitly conditioning the stochastic trajectory on the degraded input.…
SupResDiffGAN a new approach for the Super-Resolution task
Dawid Kopeć, Wojciech Kozłowski, Maciej Wizerkaniuk +3
In this work, we present SupResDiffGAN, a novel hybrid architecture that combines the strengths of Generative Adversarial Networks (GANs) and diffusion models for super-resolution…
Dimma: Semi-supervised Low Light Image Enhancement with Adaptive Dimming
Wojciech Kozłowski, Michał Szachniewicz, Michał Stypułkowski +1
Enhancing low-light images while maintaining natural colors is a challenging problem due to camera processing variations and limited access to photos with ground-truth lighting con…
Self-supervised adversarial masking for 3D point cloud representation learning
Michał Szachniewicz, Wojciech Kozłowski, Michał Stypułkowski +1
Self-supervised methods have been proven effective for learning deep representations of 3D point cloud data. Although recent methods in this domain often rely on random masking of…