相關主題
商品描述
AI-Generated Content (AIGC) is a revolutionary engine for digital content generation. In the area of art, AI has achieved remarkable advancements. AI is capable of not only creating paintings or music comparable to human masterpieces, but it also understands and appreciates artwork. For professionals and amateurs, AI is an enabling tool and an opportunity to enjoy a new world of art.
This book aims to present the state-of-the-art AI technologies for art creation, understanding, and evaluation. The contents include a survey on cross-modal generation of visual and auditory content, explainable AI and music, AI-enabled robotic theater for Chinese folk art, AI for ancient Chinese music restoration and reproduction, AI for brainwave opera, artistic text style transfer, data-driven automatic choreography, Human-AI collaborative sketching, personalized music recommendation and generation based on emotion and memory (MemoMusic), understanding music and emotion from the brain, music question answering, emotional quality evaluation for generated music, and AI for image aesthetic evaluation.
The key features of the book are as follows:
- AI for Art is a fascinating cross-disciplinary field for the academic community as well as the public.
- Each chapter is an independent interesting topic, which provides an entry for corresponding readers.
- It presents SOTA AI technologies for art creation and understanding.
- The artistry and appreciation of the book is wide-ranging - for example, the combination of AI with traditional Chinese art.
This book is dedicated to the international cross-disciplinary AI Art community: professors, students, researchers, and engineers from AI (machine learning, computer vision, multimedia computing, affective computing, robotics, etc.), art (painting, music, dance, fashion, design, etc.), cognitive science, and psychology. General audiences can also benefit from this book.
商品描述(中文翻譯)
AI 生成內容 (AIGC) 是一個革命性的數位內容生成引擎。在藝術領域，AI 已經取得了顯著的進展。AI 不僅能創作出與人類大師作品相媲美的畫作或音樂，還能理解和欣賞藝術作品。對於專業人士和業餘愛好者來說，AI 是一個促進工具，也是享受新藝術世界的機會。
本書旨在介紹最先進的 AI 技術，用於藝術創作、理解和評估。內容包括視覺和聽覺內容的跨模態生成調查、可解釋的 AI 與音樂、AI 驅動的中國民俗藝術機器人劇場、古代中國音樂的修復與再現、腦波歌劇的 AI、藝術文本風格轉換、數據驅動的自動編舞、人機協作素描、基於情感和記憶的個性化音樂推薦與生成 (MemoMusic)、從大腦理解音樂與情感、音樂問答、生成音樂的情感質量評估，以及 AI 在圖像美學評估中的應用。
本書的主要特點如下：
- AI 與藝術是一個引人入勝的跨學科領域，對學術界和公眾均具吸引力。
- 每一章都是一個獨立且有趣的主題，為相應的讀者提供了切入點。
- 本書展示了最先進的 AI 技術，用於藝術創作和理解。
- 本書的藝術性和欣賞範圍廣泛，例如，AI 與傳統中國藝術的結合。
本書獻給國際跨學科的 AI 藝術社群：來自 AI（機器學習、計算機視覺、多媒體計算、情感計算、機器人技術等）、藝術（繪畫、音樂、舞蹈、時尚、設計等）、認知科學和心理學的教授、學生、研究人員和工程師。一般讀者也能從本書中受益。
作者簡介
Luntian Mou received the Ph.D. degree in computer science from the University of Chinese Academy of Sciences, China in 2012. He accomplished as a postdoctoral Researcher with the Institute of Digital Media, Peking University, China in 2014. From 2019 to 2020, he served as a visiting scholar at Donald Bren School of Information and Computer Sciences, University of California, Irvine, USA. He is currently an associate professor with the Beijing Institute of Artificial Intelligence, Beijing University of Technology, China. His research interests include artificial intelligence, machine learning, pattern recognition, affective computing, multimedia computing, and brain-like computing. He has published on renowned journals such as TAFFC, TMM, TOMM, and ESWA. He is the recipient of Beijing Municipal Science and Technology Advancement Award, IEEE Outstanding Contribution to Standardization Award, and AVS Outstanding Contribution on 15th Anniversary Award. He serves as a guest editor for Machine Intelligence Research, and a reviewer for many important international journals and conferences such as TIP, TAFFC, TCSVT, TITS, AAAI, etc. He is a senior member of IEEE and CCF, and a member of ACM. He is the chair of the organizing committee of the 2023 CSIG Conference on Emotional Intelligence (CEI). He is the founding chair of IEEE Workshop on Artificial Intelligence for Art Creation (AIART).
作者簡介(中文翻譯)
Luntian Mou於2012年獲得中國科學院大學計算機科學博士學位。2014年，他在北京大學數字媒體研究所擔任博士後研究員。2019年至2020年，他在美國加州大學爾灣分校Donald Bren資訊與計算機科學學院擔任訪問學者。目前，他是北京工業大學北京人工智慧研究所的副教授。他的研究興趣包括人工智慧、機器學習、模式識別、情感計算、多媒體計算和類腦計算。他在TAFFC、TMM、TOMM和ESWA等知名期刊上發表過論文。他曾獲得北京市科學技術進步獎、IEEE標準化傑出貢獻獎以及AVS成立15周年傑出貢獻獎。他擔任《Machine Intelligence Research》的客座編輯，並為TIP、TAFFC、TCSVT、TITS、AAAI等多個重要國際期刊和會議擔任審稿人。他是IEEE和CCF的資深會員，以及ACM的會員。他是2023年CSIG情感智慧會議（CEI）組織委員會的主席，也是IEEE藝術創作人工智慧研討會（AIART）的創始主席。
