I am a PhD student at Skoltech in computer vision group. My supervisors are Victor Lempitsky and Andrea Vedaldi. I also work for Yandex Research.
Adversarial Generator-Encoder Networks
arXiv Tech. report
We present a new autoencoder-type architecture, that is trainable in an unsupervised mode, sustains both generation and inference, and has the quality of conditional and unconditional samples boosted by adversarial learning.
Improved Texture Networks: Maximizing Quality and Diversity in Feed-forward Stylization and Texture Synthesis
We introduce Instance Normalization for a better stylization and derive entropy loss which improves samples diversity for both texture synthesis and stylization.
Texture Networks: Feed-forward Synthesis of Textures and Stylized Images
We speed up texture synthesis and famous neural style transfer of Gatys et al. by 500 times. The method was used by such stylization apps like Prisma and Vinci.
Neural Texture Synthesis and Style Transfer for Audio
We present an extension of texture synthesis and style transfer method of Leon Gatys et al. for audio. Joint work with Vadim Lebedev.
A multicore modification of L. Van der Maaten's Barnes-Hut t-SNE with python and Torch CFFI-based wrappers. The code also works faster than sklearn.TSNE on 1 core.
Online Neural Doodle
"Fast neural doodle" + "Texture Nets" = "Online neural doodle". Feed-forward generator allows real-time applications so we've built a web demo likeMonet.
Fast Neural Doodle
Neural doodle using gram matrices matching as opposed to original patch-based method.