Computer Vision by Yixin Zhu (.PDF)
File Size: 47.5 MB
Computer Vision: Cognitive Models for Visual Commonsense by Yixin Zhu, Song-Chun Zhu
Requirements: .PDF reader, 47.5 MB
Overview: This volume on visual commonsense reasoning, part of a comprehensive three-volume series, presents a computational framework for bridging the gap between modern computer vision capabilities and human-like visual understanding. While current AI systems excel at pattern recognition tasks, they often lack the sophisticated reasoning capabilities that humans demonstrate effortlessly in understanding and interacting with their environment. This work addresses this limitation by integrating physical, social, and abstract reasoning within a unified computational framework.
The volume is organized into three parts. The first part establishes the theoretical foundations of visual commonsense through a systematic examination of physical understanding, including affordances, intuitive physics, causality, and tool use. These components form the basis for understanding how objects and environments behave and interact. The second part delves into social reasoning aspects, exploring intent, theory of mind, and nonverbal communication – crucial capabilities for AI systems to interpret and predict human behavior. The third part investigates abstract visual reasoning, examining higher-level cognitive capabilities.
Genre: Non-Fiction > Tech & Devices
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