Assignment 1 (Group): Deep art or Shallow Art
This is a group project. The goal of this project is to practice examination of artworks and to understand how your work in this class can be evaluated. You and your group members will 1) check the Depart.io website to understand how it works, 2) take pictures with your phones or cameras, 3) upload two pictures as your scene picture and style picture, respectively, to the website for the first test, 4) submit and create “style-transfer” artwork and repeat the step 3 and 4 until you have more than 10 artworks, 5) evaluate them as a group using questions from the CAN paper and questions that your group may have come up with, 6) present your group’s evaluation result and the best artwork of your group to the class, 7) submit a report describing this process and results. You cannot use any existing pictures on the website. Your group should create at least 10 artworks.
Question examples:
Q1: Communication: As I interact with this image, I feel that it is communicating with me.
Q2: Inspiration: As I interact with this image, I feel inspired and elevated.
Q3: Which image do you think is more novel?
Q4: Which image do you think is more aesthetically appealing?
Q5: Does this image give you intellectual or sensorial satisfaction?
Q6: Does this image provoke your imagination?
Q7: Does this image have a good amount of ambiguity and/or absurdity (thus it provokes you and makes you think more about the meaning of the image)?
Assignment 2 (Individual): Algorithmic Generative Art
The goal of this assignment is to create an interesting visual and/or aural composition using generative techniques. Specifically using mathematical formulas through coding to drive a system that generates the art. For this assignment you do not need to use any machine learning methods (yet) but explore what is possible through procedural code. This practice explores the natural connection between art and mathematics to establish a solid ground for your interdisciplinary projects in this class . You can choose any mathematical algorithms and methods. You can use any programming languages or tools. Any length of work is acceptable. You composition should be original and successful in terms of traditional visual art and/or music standards. You will present your project in the class and submit a report and a documentation of the work.
Assignment 4 (Group): Paper Presentation
This is a group assignment. Each group should choose a paper that introduces interesting concept and techniques at the intersection of Art and Machine Learning. This paper should not be one of reading materials in this class. Please check your choice of paper is not in our reading list. Then instructors should approve the paper you choose. You can submit your choice anytime between the beginning of the semester and three weeks before the presentation (Feb 8th). Your group will present the study result during the midterm period (March 7th and 9th) in the class. Your presentation should include introduction, motivation, methods, and results. All group members should equally participate in both study and presentation. Reproducing the results of the paper will earn extra points.
Assignment 3 (Group - recommended): Dreams or Nightmares, Artist or Assistant
Please make a visual art project using one or more ML methods that we study in the class. You will submit the project result(s) and a report that describes your concept, trials and errors (process), collaboration experience, and self-evaluation of the results. The novelty of your method will earn extra points. Each group member should have equal amount of contribution to the project and the details of each contribution should be described in the report.
For example,
surrealistic images using one or more of ML methods. The final image should be high resolution, e.g, 1k~5k. The image should be original, have successful composition, and bring the viewer meaningful questions or impressions.
Or
generating a new set of images describing a thing or a creature that may not be found easily in the world in collaboration with artificial neural networks. For example; a new face, a new chair design, a new type of letter, a new kind of animal, and so on. You can choose any kind of dataset and train them. You can download or collect your dataset. The resolution of the final images should be bigger than 256 X 256 pixels. Consider and apply your concept, the meaning of suggesting the generated form to the world, in every step of your practice from the choice of the dataset to the decisions of selecting parameters of layers.
Assignment 5 (Individual): Reincarnation or Copycat, Poetry or Gibberish
Please make an art project that progresses over time. You will submit a documentation and a report that describes concept, process, technical architecture of your work, and your evaluation of the result. Innovative approach will earn extra points.
For example,
A piece of music, speech, or soundscape using ML methods. The recommended length of this piece is less than 5 minutes. This piece should be appealing to the audience in one or more number of ways such as being pleasant, being provocative, being sublime, or creating auditory illusion. This piece can be accompanied by visual elements if needed.
Or
A piece of literature. It can be poetry, short story, lyrics, or a script. In any form, the piece should have poetic or imaginative style of expression rather than meaningless gibberish.
Assignment 6 (Group): Final project
For your final project, you can create any form of art using ML methods. Your project can partially use any of previous projects in this class as well as any of your work that was not done in the class. It should be completed as an artwork, be technically elegant, and inspire the audience. It will be presented as a part of the group exhibition at the end of the semester. Your proactive participation in the exhibition preparation, installation, and management will be counted towards the completion of the project. Your group will submit a video documentation of your work. Also a group report that describes the concept, trials and errors, technical achievements, audience feedback, and self-evaluation should be submitted during the exam week.