573 citations · 5.3k across the 57 of their papers we have counts for
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Transframer: Arbitrary Frame Prediction with Generative Models
Charlie Nash, João Carreira, Jacob Walker +4
We present a general-purpose framework for image modelling and vision tasks based on probabilistic frame prediction. Our approach unifies a broad range of tasks, from image segment…
Generating Images with Sparse Representations
Charlie Nash, Jacob Menick, Sander Dieleman +1
The high dimensionality of images presents architecture and sampling-efficiency challenges for likelihood-based generative models. Previous approaches such as VQ-VAE use deep autoe…
Learning Visual Question Answering by Bootstrapping Hard Attention
Mateusz Malinowski, Carl Doersch, Adam Santoro +1
Attention mechanisms in biological perception are thought to select subsets of perceptual information for more sophisticated processing which would be prohibitive to perform on all…
Visual Interaction Networks
Nicholas Watters, Andrea Tacchetti, Theophane Weber +3
From just a glance, humans can make rich predictions about the future state of a wide range of physical systems. On the other hand, modern approaches from engineering, robotics, an…
Unsupervised Learning of 3D Structure from Images
Danilo Jimenez Rezende, S. M. Ali Eslami, Shakir Mohamed +3
A key goal of computer vision is to recover the underlying 3D structure from 2D observations of the world. In this paper we learn strong deep generative models of 3D structures, an…