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11 papers · 1 filter
Asynchronous Temporal Fields for Action Recognition
Gunnar A. Sigurdsson, Santosh Divvala, Ali Farhadi +1
Actions are more than just movements and trajectories: we cook to eat and we hold a cup to drink from it. A thorough understanding of videos requires going beyond appearance modeli…
Knowledge Completion for Generics using Guided Tensor Factorization
Hanie Sedghi, Ashish Sabharwal
Given a knowledge base or KB containing (noisy) facts about common nouns or generics, such as "all trees produce oxygen" or "some animals live in forests", we consider the problem…
ActionFlowNet: Learning Motion Representation for Action Recognition
Joe Yue-Hei Ng, Jonghyun Choi, Jan Neumann +1
Even with the recent advances in convolutional neural networks (CNN) in various visual recognition tasks, the state-of-the-art action recognition system still relies on hand crafte…
LCNN: Lookup-based Convolutional Neural Network
Hessam Bagherinezhad, Mohammad Rastegari, Ali Farhadi
Porting state of the art deep learning algorithms to resource constrained compute platforms (e.g. VR, AR, wearables) is extremely challenging. We propose a fast, compact, and accur…
Question Answering via Integer Programming over Semi-Structured Knowledge
Daniel Khashabi, Tushar Khot, Ashish Sabharwal +3
Answering science questions posed in natural language is an important AI challenge. Answering such questions often requires non-trivial inference and knowledge that goes beyond fac…
Moving Beyond the Turing Test with the Allen AI Science Challenge
Carissa Schoenick, Peter Clark, Oyvind Tafjord +2
Given recent successes in AI (e.g., AlphaGo's victory against Lee Sedol in the game of GO), it's become increasingly important to assess: how close are AI systems to human-level in…