Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Grishchenko, Ivan"'
Autor:
Gemma Team, Mesnard, Thomas, Hardin, Cassidy, Dadashi, Robert, Bhupatiraju, Surya, Pathak, Shreya, Sifre, Laurent, Rivière, Morgane, Kale, Mihir Sanjay, Love, Juliette, Tafti, Pouya, Hussenot, Léonard, Sessa, Pier Giuseppe, Chowdhery, Aakanksha, Roberts, Adam, Barua, Aditya, Botev, Alex, Castro-Ros, Alex, Slone, Ambrose, Héliou, Amélie, Tacchetti, Andrea, Bulanova, Anna, Paterson, Antonia, Tsai, Beth, Shahriari, Bobak, Lan, Charline Le, Choquette-Choo, Christopher A., Crepy, Clément, Cer, Daniel, Ippolito, Daphne, Reid, David, Buchatskaya, Elena, Ni, Eric, Noland, Eric, Yan, Geng, Tucker, George, Muraru, George-Christian, Rozhdestvenskiy, Grigory, Michalewski, Henryk, Tenney, Ian, Grishchenko, Ivan, Austin, Jacob, Keeling, James, Labanowski, Jane, Lespiau, Jean-Baptiste, Stanway, Jeff, Brennan, Jenny, Chen, Jeremy, Ferret, Johan, Chiu, Justin, Mao-Jones, Justin, Lee, Katherine, Yu, Kathy, Millican, Katie, Sjoesund, Lars Lowe, Lee, Lisa, Dixon, Lucas, Reid, Machel, Mikuła, Maciej, Wirth, Mateo, Sharman, Michael, Chinaev, Nikolai, Thain, Nithum, Bachem, Olivier, Chang, Oscar, Wahltinez, Oscar, Bailey, Paige, Michel, Paul, Yotov, Petko, Chaabouni, Rahma, Comanescu, Ramona, Jana, Reena, Anil, Rohan, McIlroy, Ross, Liu, Ruibo, Mullins, Ryan, Smith, Samuel L, Borgeaud, Sebastian, Girgin, Sertan, Douglas, Sholto, Pandya, Shree, Shakeri, Siamak, De, Soham, Klimenko, Ted, Hennigan, Tom, Feinberg, Vlad, Stokowiec, Wojciech, Chen, Yu-hui, Ahmed, Zafarali, Gong, Zhitao, Warkentin, Tris, Peran, Ludovic, Giang, Minh, Farabet, Clément, Vinyals, Oriol, Dean, Jeff, Kavukcuoglu, Koray, Hassabis, Demis, Ghahramani, Zoubin, Eck, Douglas, Barral, Joelle, Pereira, Fernando, Collins, Eli, Joulin, Armand, Fiedel, Noah, Senter, Evan, Andreev, Alek, Kenealy, Kathleen
This work introduces Gemma, a family of lightweight, state-of-the art open models built from the research and technology used to create Gemini models. Gemma models demonstrate strong performance across academic benchmarks for language understanding,
Externí odkaz:
http://arxiv.org/abs/2403.08295
Autor:
Grishchenko, Ivan, Yan, Geng, Bazavan, Eduard Gabriel, Zanfir, Andrei, Chinaev, Nikolai, Raveendran, Karthik, Grundmann, Matthias, Sminchisescu, Cristian
We present Blendshapes GHUM, an on-device ML pipeline that predicts 52 facial blendshape coefficients at 30+ FPS on modern mobile phones, from a single monocular RGB image and enables facial motion capture applications like virtual avatars. Our main
Externí odkaz:
http://arxiv.org/abs/2309.05782
Autor:
Grishchenko, Ivan, Bazarevsky, Valentin, Zanfir, Andrei, Bazavan, Eduard Gabriel, Zanfir, Mihai, Yee, Richard, Raveendran, Karthik, Zhdanovich, Matsvei, Grundmann, Matthias, Sminchisescu, Cristian
We present BlazePose GHUM Holistic, a lightweight neural network pipeline for 3D human body landmarks and pose estimation, specifically tailored to real-time on-device inference. BlazePose GHUM Holistic enables motion capture from a single RGB image
Externí odkaz:
http://arxiv.org/abs/2206.11678
Autor:
Ablavatski, Artsiom, Vakunov, Andrey, Grishchenko, Ivan, Raveendran, Karthik, Zhdanovich, Matsvei
We present a simple, real-time approach for pupil tracking from live video on mobile devices. Our method extends a state-of-the-art face mesh detector with two new components: a tiny neural network that predicts positions of the pupils in 2D, and a d
Externí odkaz:
http://arxiv.org/abs/2006.11341
Autor:
Grishchenko, Ivan, Ablavatski, Artsiom, Kartynnik, Yury, Raveendran, Karthik, Grundmann, Matthias
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-time on-device inference and runs at over 50 FPS on a Pixel 2 phone. Our
Externí odkaz:
http://arxiv.org/abs/2006.10962
Autor:
Bazarevsky, Valentin, Grishchenko, Ivan, Raveendran, Karthik, Zhu, Tyler, Zhang, Fan, Grundmann, Matthias
We present BlazePose, a lightweight convolutional neural network architecture for human pose estimation that is tailored for real-time inference on mobile devices. During inference, the network produces 33 body keypoints for a single person and runs
Externí odkaz:
http://arxiv.org/abs/2006.10204
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 dense mesh model of 468 vertices is well-suited for face-based AR eff
Externí odkaz:
http://arxiv.org/abs/1907.06724
Autor:
Khokhlov, Nikolai, Grishchenko, Ivan, Shevelkina, Ekaterina, Bindyug, Denis, Barkanova, Ekaterina, Denisov, Dmitry, Demushkin, Dmitry, Telegin, Ivan, Yezhikova, Ekaterina, Avetissov, Igor, Avetisov, Roman, Konyashkin, Alexey, Ryabushkin, Oleg
Publikováno v:
Crystals (2073-4352); Sep2024, Vol. 14 Issue 9, p792, 11p
Publikováno v:
Економічний вісник університету / University Economic Bulletin. 1(36):74-86
Externí odkaz:
https://www.ceeol.com/search/article-detail?id=698273
Akademický článek
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