343 citations · 853 across the 13 of their papers we have counts for
22 papers
Vector Quantized Models for Planning
Sherjil Ozair, Yazhe Li, Ali Razavi +3
Recent developments in the field of model-based RL have proven successful in a range of environments, especially ones where planning is essential. However, such successes have been…
Divide and Contrast: Self-supervised Learning from Uncurated Data
Yonglong Tian, Olivier J. Henaff, Aaron van den Oord
Self-supervised learning holds promise in leveraging large amounts of unlabeled data, however much of its progress has thus far been limited to highly curated pre-training data suc…
Multimodal Self-Supervised Learning of General Audio Representations
Luyu Wang, Pauline Luc, Adria Recasens +2
We present a multimodal framework to learn general audio representations from videos. Existing contrastive audio representation learning methods mainly focus on using the audio mod…
Multi-Format Contrastive Learning of Audio Representations
Luyu Wang, Aaron van den Oord
Recent advances suggest the advantage of multi-modal training in comparison with single-modal methods. In contrast to this view, in our work we find that similar gain can be obtain…
Predicting Video with VQVAE
Jacob Walker, Ali Razavi, Aäron van den Oord
In recent years, the task of video prediction-forecasting future video given past video frames-has attracted attention in the research community. In this paper we propose a novel a…
Broaden Your Views for Self-Supervised Video Learning
Adrià Recasens, Pauline Luc, Jean-Baptiste Alayrac +11
Most successful self-supervised learning methods are trained to align the representations of two independent views from the data. State-of-the-art methods in video are inspired by…