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Natural Questions: a New Corpus and Challenge for Question Answering Research
To help spur research advances in QA, we are excited to announce Natural Questions (NQ), a new, large-scale corpus for training and evaluating open-domain question answering systems, and the first to replicate the end-to-end process in which people find answers to questions.
(Google AI) / (Paper)
Facebook Open Sources
Zero-shot Transfer across 93 Languages: Open-sourcing Enhanced LASER library
Binary Image Selection (BISON): Interpretable Evaluation of Visual Grounding / (GitHub)
A New Predictive Model for More Accurate Electrical Grid Mapping / (GitHub)
Announcing CheXpert, Large Dataset of Chest X-rays Co-released with MIT’s MIMIC-CXR Dataset
CheXpert is a large dataset of chest X-rays and competition for automated chest x-ray interpretation, which features uncertainty labels and radiologist-labeled reference standard evaluation sets.
(Stanford Machine Learning Group) / (Paper)
AlphaStar: Mastering the Real-Time Strategy Game StarCraft II
Now, we introduce our StarCraft II program AlphaStar, the first Artificial Intelligence to defeat a top professional player. In a series of test matches held on 19 December, AlphaStar decisively beat Team Liquid’s Grzegorz “MaNa” Komincz, one of the world’s strongest professional StarCraft players, 5-0, following a successful benchmark match against his team-mate Dario “TLO” Wünsch. The matches took place under professional match conditions on a competitive ladder map and without any game restrictions.
(DeepMind) / (Synced)
Filling Holes: Adobe Proposes Foreground-Aware Image Inpainting
Existing image inpainting methods fill holes by borrowing information from surrounding image regions. These methods however produce unsatisfactory results if holes overlap with foreground objects, suffering from a “lack of information about the actual extent of foreground and background regions with the holes.”
3D Human Pose Machines with Self-supervised Learning
This paper proposes a simple yet effective self-supervised correction mechanism to learn all intrinsic structures of human poses from abundant images. Specifically, the proposed mechanism involves two dual learning tasks, i.e., the 2D-to-3D pose transformation and 3D-to-2D pose projection, to serve as a bridge between 3D and 2D human poses in a type of “free” self-supervision for accurate 3D human pose estimation.
(Sun Yat-sen University & SenseTime Group)
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Global AI Events
Jan 27 – Feb 1, 2019 AAAI 2019: Association for the Advancement of Artificial Intelligence. Hawaii, United State
March 17 – 20, ACM IUI. Los Angeles, United States
Global AI Opportunities
2019 Google AI Residency Program
Research Scientist, Google Brain Toronto
Microsoft AI Residency Program
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