Artificial Intelligence for Art Creation and Understanding
Herausgeber: Mou, Luntian
Artificial Intelligence for Art Creation and Understanding
Herausgeber: Mou, Luntian
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This book covers state-of-the-art AI technologies for art creation, understanding, and evaluation. Each chapter providing an entry point for readers, presenting SOTA AI technologies for art creation and understanding and covering the fascinating combination of AI with traditional Chinese art.
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This book covers state-of-the-art AI technologies for art creation, understanding, and evaluation. Each chapter providing an entry point for readers, presenting SOTA AI technologies for art creation and understanding and covering the fascinating combination of AI with traditional Chinese art.
Produktdetails
- Produktdetails
- Verlag: Taylor & Francis Ltd
- Seitenzahl: 312
- Erscheinungstermin: 29. August 2024
- Englisch
- Abmessung: 234mm x 156mm
- ISBN-13: 9781032523606
- ISBN-10: 1032523603
- Artikelnr.: 70146661
- Verlag: Taylor & Francis Ltd
- Seitenzahl: 312
- Erscheinungstermin: 29. August 2024
- Englisch
- Abmessung: 234mm x 156mm
- ISBN-13: 9781032523606
- ISBN-10: 1032523603
- Artikelnr.: 70146661
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).
Chapter 1. Explainable AI and Music
Chapter 2. AI Enabled Robotic Theatres for Chinese Folk Art
Chapter 3. AIBO - Or How to Make a 'Sicko' Brainwave Opera
Chapter 4. Cross-modal Generation of Visual and Auditory Content: A Survey
Chapter 5. Artistic Text Style Transfer
Chapter 6. Data-driven Automatic Choreography
Chapter 7. Toward Human-AI Collaborative Sketching
Chapter 8. MemoMusic: A Personalized Music Recommendation and Generation
Framework Based on Emotion and Memory
Chapter 9. Algorithmic Composition for Ancient Chinese Music Restoration
and Reproduction - A Melody Generator Approach
Chapter 10. Understanding Music and Emotion from Brain
Chapter 11. Music Question Answering: Cognize and Perceive Music
Chapter 12. Emotional Quality Evaluation for Generated Music
Chapter 13. A Deep Drift-Diffusion Model for Image Aesthetic Score
Distribution Prediction
Chapter 2. AI Enabled Robotic Theatres for Chinese Folk Art
Chapter 3. AIBO - Or How to Make a 'Sicko' Brainwave Opera
Chapter 4. Cross-modal Generation of Visual and Auditory Content: A Survey
Chapter 5. Artistic Text Style Transfer
Chapter 6. Data-driven Automatic Choreography
Chapter 7. Toward Human-AI Collaborative Sketching
Chapter 8. MemoMusic: A Personalized Music Recommendation and Generation
Framework Based on Emotion and Memory
Chapter 9. Algorithmic Composition for Ancient Chinese Music Restoration
and Reproduction - A Melody Generator Approach
Chapter 10. Understanding Music and Emotion from Brain
Chapter 11. Music Question Answering: Cognize and Perceive Music
Chapter 12. Emotional Quality Evaluation for Generated Music
Chapter 13. A Deep Drift-Diffusion Model for Image Aesthetic Score
Distribution Prediction
Chapter 1. Explainable AI and Music
Chapter 2. AI Enabled Robotic Theatres for Chinese Folk Art
Chapter 3. AIBO - Or How to Make a 'Sicko' Brainwave Opera
Chapter 4. Cross-modal Generation of Visual and Auditory Content: A Survey
Chapter 5. Artistic Text Style Transfer
Chapter 6. Data-driven Automatic Choreography
Chapter 7. Toward Human-AI Collaborative Sketching
Chapter 8. MemoMusic: A Personalized Music Recommendation and Generation
Framework Based on Emotion and Memory
Chapter 9. Algorithmic Composition for Ancient Chinese Music Restoration
and Reproduction - A Melody Generator Approach
Chapter 10. Understanding Music and Emotion from Brain
Chapter 11. Music Question Answering: Cognize and Perceive Music
Chapter 12. Emotional Quality Evaluation for Generated Music
Chapter 13. A Deep Drift-Diffusion Model for Image Aesthetic Score
Distribution Prediction
Chapter 2. AI Enabled Robotic Theatres for Chinese Folk Art
Chapter 3. AIBO - Or How to Make a 'Sicko' Brainwave Opera
Chapter 4. Cross-modal Generation of Visual and Auditory Content: A Survey
Chapter 5. Artistic Text Style Transfer
Chapter 6. Data-driven Automatic Choreography
Chapter 7. Toward Human-AI Collaborative Sketching
Chapter 8. MemoMusic: A Personalized Music Recommendation and Generation
Framework Based on Emotion and Memory
Chapter 9. Algorithmic Composition for Ancient Chinese Music Restoration
and Reproduction - A Melody Generator Approach
Chapter 10. Understanding Music and Emotion from Brain
Chapter 11. Music Question Answering: Cognize and Perceive Music
Chapter 12. Emotional Quality Evaluation for Generated Music
Chapter 13. A Deep Drift-Diffusion Model for Image Aesthetic Score
Distribution Prediction