The recent increase in popularity of volumetric representations for scene reconstruction and novel view synthesis has put renewed focus on animating volumetric content at high visual quality and in real-time.
no code implementations • 6 Apr 2022 • Erroll Wood, Tadas Baltrusaitis, Charlie Hewitt, Matthew Johnson, Jingjing Shen, Nikola Milosavljevic, Daniel Wilde, Stephan Garbin, Chirag Raman, Jamie Shotton, Toby Sharp, Ivan Stojiljkovic, Tom Cashman, Julien Valentin
By fitting a morphable model to these dense landmarks, we achieve state-of-the-art results for monocular 3D face reconstruction in the wild.
no code implementations • 2 Feb 2022 • Aidan Clark, Diego de Las Casas, Aurelia Guy, Arthur Mensch, Michela Paganini, Jordan Hoffmann, Bogdan Damoc, Blake Hechtman, Trevor Cai, Sebastian Borgeaud, George van den Driessche, Eliza Rutherford, Tom Hennigan, Matthew Johnson, Katie Millican, Albin Cassirer, Chris Jones, Elena Buchatskaya, David Budden, Laurent SIfre, Simon Osindero, Oriol Vinyals, Jack Rae, Erich Elsen, Koray Kavukcuoglu, Karen Simonyan
The performance of a language model has been shown to be effectively modeled as a power-law in its parameter count.
no code implementations • • Jack W. Rae, Sebastian Borgeaud, Trevor Cai, Katie Millican, Jordan Hoffmann, Francis Song, John Aslanides, Sarah Henderson, Roman Ring, Susannah Young, Eliza Rutherford, Tom Hennigan, Jacob Menick, Albin Cassirer, Richard Powell, George van den Driessche, Lisa Anne Hendricks, Maribeth Rauh, Po-Sen Huang, Amelia Glaese, Johannes Welbl, Sumanth Dathathri, Saffron Huang, Jonathan Uesato, John Mellor, Irina Higgins, Antonia Creswell, Nat McAleese, Amy Wu, Erich Elsen, Siddhant Jayakumar, Elena Buchatskaya, David Budden, Esme Sutherland, Karen Simonyan, Michela Paganini, Laurent SIfre, Lena Martens, Xiang Lorraine Li, Adhiguna Kuncoro, Aida Nematzadeh, Elena Gribovskaya, Domenic Donato, Angeliki Lazaridou, Arthur Mensch, Jean-Baptiste Lespiau, Maria Tsimpoukelli, Nikolai Grigorev, Doug Fritz, Thibault Sottiaux, Mantas Pajarskas, Toby Pohlen, Zhitao Gong, Daniel Toyama, Cyprien de Masson d'Autume, Yujia Li, Tayfun Terzi, Vladimir Mikulik, Igor Babuschkin, Aidan Clark, Diego de Las Casas, Aurelia Guy, Chris Jones, James Bradbury, Matthew Johnson, Blake Hechtman, Laura Weidinger, Iason Gabriel, William Isaac, Ed Lockhart, Simon Osindero, Laura Rimell, Chris Dyer, Oriol Vinyals, Kareem Ayoub, Jeff Stanway, Lorrayne Bennett, Demis Hassabis, Koray Kavukcuoglu, Geoffrey Irving
Language modelling provides a step towards intelligent communication systems by harnessing large repositories of written human knowledge to better predict and understand the world.
Ranked #1 on Abstract Algebra on BIG-bench
We demonstrate that it is possible to perform face-related computer vision in the wild using synthetic data alone.
Ranked #2 on Face Parsing on Helen (using extra training data)
Recent work on Neural Radiance Fields (NeRF) showed how neural networks can be used to encode complex 3D environments that can be rendered photorealistically from novel viewpoints.
no code implementations • 22 Dec 2020 • Adam D. Hincks, Simone Aiola, J. Richard Bond, Erminia Calabrese, Andrei Frolov, José Tomás Gálvez Ghersi, Renée Hložek, Matthew Johnson, Mathew S. Madhavacheril, Moritz Münchmeyer, Lyman A. Page, Jonathan Sievers, Suzanne T. Staggs, Alexander van Engelen
Observations of the cosmic microwave background (CMB) are an incredibly fertile source of information for studying the origins and evolution of the Universe.
Instrumentation and Methods for Astrophysics Cosmology and Nongalactic Astrophysics
no code implementations • 3 Nov 2020 • Emil Annevelink, Rachel Kurchin, Eric Muckley, Lance Kavalsky, Vinay I. Hegde, Valentin Sulzer, Shang Zhu, Jiankun Pu, David Farina, Matthew Johnson, Dhairya Gandhi, Adarsh Dave, Hongyi Lin, Alan Edelman, Bharath Ramsundar, James Saal, Christopher Rackauckas, Viral Shah, Bryce Meredig, Venkatasubramanian Viswanathan
Large-scale electrification is vital to addressing the climate crisis, but several scientific and technological challenges remain to fully electrify both the chemical industry and transportation.
For the Odd Cycle Transversal problem, the task is to find a small set $S$ of vertices in a graph that intersects every cycle of odd length.
Data Structures and Algorithms Discrete Mathematics Combinatorics
Analysis of faces is one of the core applications of computer vision, with tasks ranging from landmark alignment, head pose estimation, expression recognition, and face recognition among others.
In contrast to computer graphics approaches, generative models learned from more readily available 2D image data have been shown to produce samples of human faces that are hard to distinguish from real data.
Our ability to sample realistic natural images, particularly faces, has advanced by leaps and bounds in recent years, yet our ability to exert fine-tuned control over the generative process has lagged behind.
This paper has been withdrawn by the authors due to insufficient or definition error(s) in the ethics approval protocol.
For both a state-of-the-art VAE on 64x64 ImageNet and Image Transformer on 256x256 CelebA-HQ, our approach achieves an optimal linear speedup from 1 to 256 TPUv2 chips.
Most of the current literature in these fields involve visualizing the time-series for noticeable structure and hard coding them into pre-specified parametric functions.
We propose the segmented iHMM (siHMM), a hierarchical infinite hidden Markov model (iHMM) that supports a simple, efficient inference scheme.
For example, nucleotides in a DNA sequence, children's names in a given state and year, and text documents are all commonly modeled with multinomial distributions.
In this paper, we present an algorithm for optimizing the split functions at all levels of the tree jointly with the leaf parameters, based on a global objective.
Sampling inference methods are computationally difficult to scale for many models in part because global dependencies can reduce opportunities for parallel computation.