2 code implementations • NeurIPS 2023 • Viorica Pătrăucean, Lucas Smaira, Ankush Gupta, Adrià Recasens Continente, Larisa Markeeva, Dylan Banarse, Skanda Koppula, Joseph Heyward, Mateusz Malinowski, Yi Yang, Carl Doersch, Tatiana Matejovicova, Yury Sulsky, Antoine Miech, Alex Frechette, Hanna Klimczak, Raphael Koster, Junlin Zhang, Stephanie Winkler, Yusuf Aytar, Simon Osindero, Dima Damen, Andrew Zisserman, João Carreira
We propose a novel multimodal video benchmark - the Perception Test - to evaluate the perception and reasoning skills of pre-trained multimodal models (e. g. Flamingo, SeViLA, or GPT-4).
no code implementations • 13 Jan 2023 • Pol Moreno, Adam R. Kosiorek, Heiko Strathmann, Daniel Zoran, Rosalia G. Schneider, Björn Winckler, Larisa Markeeva, Théophane Weber, Danilo J. Rezende
NeRF provides unparalleled fidelity of novel view synthesis: rendering a 3D scene from an arbitrary viewpoint.
3 code implementations • 7 Nov 2022 • Carl Doersch, Ankush Gupta, Larisa Markeeva, Adrià Recasens, Lucas Smaira, Yusuf Aytar, João Carreira, Andrew Zisserman, Yi Yang
Generic motion understanding from video involves not only tracking objects, but also perceiving how their surfaces deform and move.
1 code implementation • Deep Mind 2022 • Viorica Pătrăucean, Lucas Smaira, Ankush Gupta, Adrià Recasens Continente, Larisa Markeeva, Dylan Banarse, Mateusz Malinowski, Yi Yang, Carl Doersch, Tatiana Matejovicova, Yury Sulsky, Antoine Miech, Skanda Koppula, Alex Frechette, Hanna Klimczak, Raphael Koster, Junlin Zhang, Stephanie Winkler, Yusuf Aytar, Simon Osindero, Dima Damen, Andrew Zisserman and João Carreira
We propose a novel multimodal benchmark – the Perception Test – that aims to extensively evaluate perception and reasoning skills of multimodal models.
no code implementations • 3 Jul 2021 • Ibrahim Alabdulmohsin, Larisa Markeeva, Daniel Keysers, Ilya Tolstikhin
We introduce a generalization to the lottery ticket hypothesis in which the notion of "sparsity" is relaxed by choosing an arbitrary basis in the space of parameters.
3 code implementations • CVPR 2022 • Lucas Beyer, Xiaohua Zhai, Amélie Royer, Larisa Markeeva, Rohan Anil, Alexander Kolesnikov
In particular, we uncover that there are certain implicit design choices, which may drastically affect the effectiveness of distillation.
Ranked #453 on Image Classification on ImageNet
1 code implementation • ICLR Workshop DeepDiffEq 2019 • Julia Gusak, Larisa Markeeva, Talgat Daulbaev, Alexandr Katrutsa, Andrzej Cichocki, Ivan Oseledets
Normalization is an important and vastly investigated technique in deep learning.
1 code implementation • NeurIPS 2020 • Talgat Daulbaev, Alexandr Katrutsa, Larisa Markeeva, Julia Gusak, Andrzej Cichocki, Ivan Oseledets
We propose a simple interpolation-based method for the efficient approximation of gradients in neural ODE models.
3 code implementations • 24 Mar 2019 • Julia Gusak, Maksym Kholiavchenko, Evgeny Ponomarev, Larisa Markeeva, Ivan Oseledets, Andrzej Cichocki
The low-rank tensor approximation is very promising for the compression of deep neural networks.