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Christian Riess

4 accepted papers

2021

Deep Learning Architectural Designs for Super-Resolution Of Noisy Images

ICASSP 2021accepted

Recent advances in deep learning have led to significant improvements in single image super-resolution (SR) research. However, due to the amplification of noise during the upsampling steps, state-of-the-art methods often fail at reconstructing high-resolution images from noisy versions of their low-…

Cited by 0SourceScholar
2019

FaceForensics++: Learning to Detect Manipulated Facial Images

ICCV 2019poster

The rapid progress in synthetic image generation and manipulation has now come to a point where it raises significant concerns for the implications towards society. At best, this leads to a loss of trust in digital content, but could potentially cause further harm by spreading false information or f…

Cited by 2929PDFcodeScholar
2019

Towards Learned Color Representations for Image Splicing Detection

ICASSP 2019accepted

The detection of images that are spliced from multiple sources is one important goal of image forensics. Several methods have been proposed for this task, but particularly since the rise of social media, it is an ongoing challenge to devise forensic approaches that are highly robust to common proces…

Cited by 0SourceScholar