8 citations · 15 across the 11 of their papers we have counts for
4 papers · 1 filter
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.…
Pre-Pruning and Gradient-Dropping Improve Differentially Private Image Classification
Kamil Adamczewski, Yingchen He, Mijung Park
Scalability is a significant challenge when it comes to applying differential privacy to training deep neural networks. The commonly used DP-SGD algorithm struggles to maintain a h…