Computer Vision: Cognitive Models for Visual Commonsense
暫譯: 電腦視覺：視覺常識的認知模型

Yixin Zhu is a Boya Assistant Professor at the Institute for Artificial Intelligence, Peking University, where he serves as Assistant Dean. Dr. Zhu received his Ph.D. in Statistics from the University of California, Los Angeles (2018), advised by Professor Song-Chun Zhu. His research aims to construct interactive AI systems by fusing high-level common sense---including functionality, affordance, intuitive physics, causality, and intent---with raw sensory data such as pixels and haptic signals. This interdisciplinary approach seeks to endow machines with sophisticated representations and robust reasoning capabilities across objects, scenes, shapes, numbers, and intelligent agents.

Song-Chun Zhu is a distinguished computer scientist specializing in computer vision, cognitive AI, and robotics. He received his B.S. from the University of Science and Technology of China (1991) and Ph.D. from Harvard University (1996). After positions at Stanford University and Ohio State University, he served as professor at UCLA (2002-2020), where he directed the Center for Vision, Cognition, Learning and Autonomy. Since 2020, he has been Chair Professor at Peking University and Tsinghua University, directing the Beijing Institute for General Artificial Intelligence (BIGAI). His pioneering work includes the FRAME model, stochastic grammar, and cognitive AI frameworks integrating visual commonsense reasoning. His contributions have earned him numerous accolades, including the David Marr Prize (2003), J.K. Aggarwal Prize (2008), and IEEE Fellow (2011). Through his research, institution building, and leadership in major conferences, Dr. Zhu continues to advance the development of interpretable and generalizable AI systems that bridge computational approaches with human-like reasoning.

朱毅新是北京大學人工智慧研究所的博雅助理教授，並擔任助理院長。朱博士於加州大學洛杉磯分校獲得統計學博士學位（2018年），指導教授為朱松純教授。他的研究旨在通過將高層次的常識——包括功能性、可供性、直觀物理學、因果關係和意圖——與原始感官數據（如像素和觸覺信號）融合，來構建互動式人工智慧系統。這種跨學科的方法旨在賦予機器複雜的表徵和穩健的推理能力，涵蓋物體、場景、形狀、數字和智能代理。

朱松純是一位傑出的計算機科學家，專注於計算機視覺、認知人工智慧和機器人技術。他於中國科學技術大學獲得學士學位（1991年）和哈佛大學獲得博士學位（1996年）。在斯坦福大學和俄亥俄州立大學任職後，他於加州大學洛杉磯分校擔任教授（2002-2020年），並主導視覺、認知、學習與自主中心。自2020年以來，他擔任北京大學和清華大學的講座教授，並主導北京通用人工智慧研究院（BIGAI）。他的開創性工作包括FRAME模型、隨機文法和整合視覺常識推理的認知人工智慧框架。他的貢獻為他贏得了眾多榮譽，包括大衛·馬爾獎（2003年）、J.K. Aggarwal獎（2008年）和IEEE Fellow（2011年）。通過他的研究、機構建設和在主要會議中的領導，朱博士持續推進可解釋和可泛化的人工智慧系統的發展，將計算方法與類人推理相結合。