65 citations · 127 across the 13 of their papers we have counts for
4 papers · 1 filter
Accurate Compression of Text-to-Image Diffusion Models via Vector Quantization
Vage Egiazarian, Denis Kuznedelev, Anton Voronov +5
Text-to-image diffusion models have emerged as a powerful framework for high-quality image generation given textual prompts. Their success has driven the rapid development of produ…
Deep Vectorization of Technical Drawings
Vage Egiazarian, Oleg Voynov, Alexey Artemov +5
We present a new method for vectorization of technical line drawings, such as floor plans, architectural drawings, and 2D CAD images. Our method includes (1) a deep learning-based…
Latent-Space Laplacian Pyramids for Adversarial Representation Learning with 3D Point Clouds
Vage Egiazarian, Savva Ignatyev, Alexey Artemov +5
Constructing high-quality generative models for 3D shapes is a fundamental task in computer vision with diverse applications in geometry processing, engineering, and design. Despit…
Perceptual deep depth super-resolution
Oleg Voynov, Alexey Artemov, Vage Egiazarian +4
RGBD images, combining high-resolution color and lower-resolution depth from various types of depth sensors, are increasingly common. One can significantly improve the resolution o…