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CS 585

Deep Generative Networks

CS 585 is about getting deep networks to *produce* images and video rather than just classify them — learning the distribution of pixels well enough to synthesize, translate, inpaint, or extend them. Most of the weight sits on a semester-long project plus a presentation and report, with a midterm and final framing the theory behind GANs, transformers, and self-supervised reconstruction. It assumes you're comfortable with CNNs and basic deep learning from CS 464/484, and it's the natural follow-up if you want to do research in vision, multimodal models, or anything generative downstream.

Credit3ECTS5FacultyFaculty of EngineeringBölümComputer Engineering

Haftalık müfredat 14 hafta

Hafta 1
Introduction to Deep Generative Networks
Hafta 2
Convolutional Neural Network Architectures
Hafta 3
Generative Adversarial Networks
Hafta 4
Discovering Interpretable Latent Codes
Hafta 5
Transformers, Attention Models
Hafta 6
Image to Image Translation
Hafta 7
Multi-modal Image to Image Translation
Hafta 8
Presentations
Hafta 9
Image Inpainting
Hafta 10
Texture Synthesis
Hafta 11
Unsupervised Feature Learning via Image Reconstruction
Hafta 12
Self-supervised 3D Image Learning
Hafta 13
Video Generation
Hafta 14
Project Presentations

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