activity
20162024
most citedBlazeFace: Sub-millisecond Neural Face Detection on Mobile GPUs

250 citations · 371 across the 6 of their papers we have counts for

collaborators

6 papers

eess.AS2024★ 1 cited

StreamVC: Real-Time Low-Latency Voice Conversion

Yang Yang, Yury Kartynnik, Yunpeng Li +4

We present StreamVC, a streaming voice conversion solution that preserves the content and prosody of any source speech while matching the voice timbre from any target speech. Unlik…

cs.CV2020★ 52 cited

Attention Mesh: High-fidelity Face Mesh Prediction in Real-time

Ivan Grishchenko, Artsiom Ablavatski, Yury Kartynnik +2

We present Attention Mesh, a lightweight architecture for 3D face mesh prediction that uses attention to semantically meaningful regions. Our neural network is designed for real-ti…

cs.CV2019★ 8 cited

Real-time Hair Segmentation and Recoloring on Mobile GPUs

Andrei Tkachenka, Gregory Karpiak, Andrey Vakunov +4

We present a novel approach for neural network-based hair segmentation from a single camera input specifically designed for real-time, mobile application. Our relatively small neur…

cs.CV2019★ 58 cited

Real-time Facial Surface Geometry from Monocular Video on Mobile GPUs

Yury Kartynnik, Artsiom Ablavatski, Ivan Grishchenko +1

We present an end-to-end neural network-based model for inferring an approximate 3D mesh representation of a human face from single camera input for AR applications. The relatively…

cs.CV2019★ 250 cited

BlazeFace: Sub-millisecond Neural Face Detection on Mobile GPUs

Valentin Bazarevsky, Yury Kartynnik, Andrey Vakunov +2

We present BlazeFace, a lightweight and well-performing face detector tailored for mobile GPU inference. It runs at a speed of 200-1000+ FPS on flagship devices. This super-realtim…

cs.DM2016★ 2 cited

On Minimum Maximal Distance-k Matchings

Yury Kartynnik, Andrew Ryzhikov

We study the computational complexity of several problems connected with finding a maximal distance- matching of minimum cardinality or minimum weight in a given graph. We intro…