Planning 2023

Info pour les TP

Course 1: Computer Vision and Machine Learning basics: local image description (BoF), global image representation (BoW), and linear classification (with SVM)

Course 2: Introduction to Neural Networks, Multilayer perceptron

Course 3: Convolutional Neural Nets

Course 4: Transformers for Vision

Course 5: Transfer learning and Domain adaptation

Course 6: Segmentation with CNN and Transformers

Course 7: Generative models with GANs

Course 8: Generative models (2): diffusion models

Course 9: Large VL models: CLIP, StableDiffusion, Flamingo

Course 10: controle de cours, sur tout ce que a été traité durant le cours, rien concernant les TPs.

Further reading (available at SorbonneU library):
Book Computer Vision: Algorithms and Applications, Richard Szeliski
Book Deep Learning, I. Goodfellow, Y. Bengio, A. Courville
Book Apprentissage artificiel : Concepts et algorithmes., A. Cornuéjols, L. Miclet
Book Machine Learning Techniques for Multimedia, M. Cord, P. Cunningham (Eds.)