3.6k citations · 6.2k across the 27 of their papers we have counts for
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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…
Self-Supervised MultiModal Versatile Networks
Jean-Baptiste Alayrac, Adrià Recasens, Rosalia Schneider +6
Videos are a rich source of multi-modal supervision. In this work, we learn representations using self-supervision by leveraging three modalities naturally present in videos: visua…
Transformation-based Adversarial Video Prediction on Large-Scale Data
Pauline Luc, Aidan Clark, Sander Dieleman +4
Recent breakthroughs in adversarial generative modeling have led to models capable of producing video samples of high quality, even on large and complex datasets of real-world vide…
Hierarchical Autoregressive Image Models with Auxiliary Decoders
Jeffrey De Fauw, Sander Dieleman, Karen Simonyan
Autoregressive generative models of images tend to be biased towards capturing local structure, and as a result they often produce samples which are lacking in terms of large-scale…
Beyond Temporal Pooling: Recurrence and Temporal Convolutions for Gesture Recognition in Video
Lionel Pigou, Aäron van den Oord, Sander Dieleman +2
Recent studies have demonstrated the power of recurrent neural networks for machine translation, image captioning and speech recognition. For the task of capturing temporal structu…