28 citations · 55 across the 7 of their papers we have counts for
6 papers · 1 filter
YaART: Yet Another ART Rendering Technology
Sergey Kastryulin, Artem Konev, Alexander Shishenya +20
In the rapidly progressing field of generative models, the development of efficient and high-fidelity text-to-image diffusion systems represents a significant frontier. This study…
QUASAR: QUality and Aesthetics Scoring with Advanced Representations
Sergey Kastryulin, Denis Prokopenko, Artem Babenko +1
This paper introduces a new data-driven, non-parametric method for image quality and aesthetics assessment, surpassing existing approaches and requiring no prompt engineering or fi…
Towards Real-time Text-driven Image Manipulation with Unconditional Diffusion Models
Nikita Starodubcev, Dmitry Baranchuk, Valentin Khrulkov +1
Recent advances in diffusion models enable many powerful instruments for image editing. One of these instruments is text-driven image manipulations: editing semantic attributes of…
Label-Efficient Semantic Segmentation with Diffusion Models
Dmitry Baranchuk, Ivan Rubachev, Andrey Voynov +2
Denoising diffusion probabilistic models have recently received much research attention since they outperform alternative approaches, such as GANs, and currently provide state-of-t…
Improving Bilayer Product Quantization for Billion-Scale Approximate Nearest Neighbors in High Dimensions
Artem Babenko, Victor Lempitsky
The top-performing systems for billion-scale high-dimensional approximate nearest neighbor (ANN) search are all based on two-layer architectures that include an indexing structure…
Neural Codes for Image Retrieval
Artem Babenko, Anton Slesarev, Alexandr Chigorin +1
It has been shown that the activations invoked by an image within the top layers of a large convolutional neural network provide a high-level descriptor of the visual content of th…