CVPR Announces Best Paper Awards; ImageNet Honoured 10 Years Later

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CVPR 2019 Attracts 9K Attendees; Best Papers Announced; ImageNet Honoured 10 Years Later
Conference organizers have announced the recipient of the CVPR 2019 Best Paper Award: A Theory of Fermat Paths for Non-Line-of-Sight Shape Reconstruction from Carnegie Mellon University, University of Toronto, and University College London. The paper presents a novel theory on Fermat paths of light between a known visible scene and an unknown object not in the line of sight of a transient camera.
(Synced)

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CVPR 2019 | Synced Notable Paper Picks
– Envisioning Privacy Preserving Image-Based Localization for Augmented Reality
– A Theory of Fermat Paths for Non-Line-of-Sight Shape Reconstruction
– Neural Task Graphs: Generalizing to Unseen Tasks from A Single Video Demonstration
– Using AI to Generate Recipes from Food Images
– MediaPipe: A Framework for Perceiving and Augmenting Reality
– Using Platform-Aware AI to Design Compact and Efficient Neural Networks
– Accelerating MRI Reconstruction via Active Acqui

Technology

Functional Regularisation for Continual Learning
Researchers introduce a framework for continual learning based on Bayesian inference over the function space rather than the parameters of a deep neural network. This method, referred to as functional regularisation for continual learning, avoids forgetting a previous task by constructing and memorising an approximate posterior belief over the underlying task-specific function.
(DeepMind)

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Meta-Learning Surrogate Models for Sequential Decision Making
Researchers introduce a unified probabilistic framework for solving sequential decision making problems ranging from Bayesian optimisation to contextual bandits and reinforcement learning. This is accomplished by a probabilistic model-based approach that explains observed data while capturing predictive uncertainty during the decision making process.
(DeepMind)

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Bridging the Domain Gap for Neural Models
To understand the challenge behind domain shift and the need for domain adaptation, researchers establish a simple pilot experiment: they use the real-world house number images from SVHN dataset as one domain and the handwritten digit images from MNIST dataset as another domain.
(Apple)

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Leading Researchers Publish ‘Climate Change + AI’ Document
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Global AI Events

June 28: Research and Applied AI Summit (RAAIS) in London, United Kingdom

August 19-23: Knowledge Discovery and Data Mining (KDD2019) in London, United Kingdom

September 10-12: The AI Summit (Part of TechXLR8) in Singapore

September 24-28: Microsoft Ignite in Orlando, United States

Global AI Opportunities

Research Scientist, Google Brain Toronto

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DeepMind is Recruiting

DeepMind Scholarship: Access to Science

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LANDING AI is recruiting

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