Vision Instruction And Action
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The Interface of Language, Vision, and Action
This book brings together chapters from investigators on the leading edge on this new research area to explore on the leading edge on this new research area to explore common theoretical issues, empirical findings, technical problems, and outstanding questions. This book will serve as a blueprint for work on the interface of vision, language, and action over the next five to ten years.
Computer Vision – ECCV 2020
The 30-volume set, comprising the LNCS books 12346 until 12375, constitutes the refereed proceedings of the 16th European Conference on Computer Vision, ECCV 2020, which was planned to be held in Glasgow, UK, during August 23-28, 2020. The conference was held virtually due to the COVID-19 pandemic. The 1360 revised papers presented in these proceedings were carefully reviewed and selected from a total of 5025 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation.
Vision, Instruction, and Action
Vision, Instruction, and Action clearly and cleverly describes a sophisticated integrated system called Sonja that takes instruction, can interpret its environment visually, and can play games (in this case the video game, Amazon) on its own. Sonja integrates advances in intermediate visual processing, interactive activity, and natural language pragmatics. In demonstrating that such systems, rare in artificial intelligence, are possible, David Chapman shows how discoveries in visual psychophysics can be incorporated into Al, how complex activity can result from participation rather than plan following, and how physical context can be used to interpret indexical instructions. Sonja is able to play a competent beginner's game of Amazon autonomously and at the same time can also make flexible use of human instructions in knowing how to kill off monsters, pick up and use tools, and find its way in a dungeon maze. It extends the author's previous work in developing a new theory of activity by addressing linguistic issues and providing a better understanding of the architecture underlying activity, incorporating many technical improvements. Sonja also models several pragmatic issues in computational linguistics, focusing on external reference and including linguistic repair processing, and the use of temporal and spatial expressions. It connects language use with more detailed and realistic theories of vision and activity. In the field of vision research, Sonja provides an implementation of a unified visual architecture, demonstrating that this architecture can support a serious theory of activity. It demonstrates the first instance that various visual mechanisms previously proposed on psychophysical, neurophysiological, and speculative computational grounds can be made useful by connecting them with a natural task domain. David Chapman is a Computer Scientist with Teleos Research in Palo Alto.