8 citations · 21 across the 8 of their papers we have counts for
5 papers · 1 filter
Universal Perturbation Attack on Differentiable No-Reference Image- and Video-Quality Metrics
Ekaterina Shumitskaya, Anastasia Antsiferova, Dmitriy Vatolin
Universal adversarial perturbation attacks are widely used to analyze image classifiers that employ convolutional neural networks. Nowadays, some attacks can deceive image- and vid…
Combining Contrastive and Supervised Learning for Video Super-Resolution Detection
Viacheslav Meshchaninov, Ivan Molodetskikh, Dmitriy Vatolin
Upscaled video detection is a helpful tool in multimedia forensics, but it is a challenging task that involves various upscaling and compression algorithms. There are many resoluti…
Towards True Detail Restoration for Super-Resolution: A Benchmark and a Quality Metric
Eugene Lyapustin, Anastasia Kirillova, Viacheslav Meshchaninov +3
Super-resolution (SR) has become a widely researched topic in recent years. SR methods can improve overall image and video quality and create new possibilities for further content…
Shot boundary detection method based on a new extensive dataset and mixed features
Alexander Gushchin, Anastasia Antsiferova, Dmitriy Vatolin
Shot boundary detection in video is one of the key stages of video data processing. A new method for shot boundary detection based on several video features, such as color histogra…
Predicting video saliency using crowdsourced mouse-tracking data
Vitaliy Lyudvichenko, Dmitriy Vatolin
This paper presents a new way of getting high-quality saliency maps for video, using a cheaper alternative to eye-tracking data. We designed a mouse-contingent video viewing system…