COV877: Special Module on Visual Computing

The generation of visual content is a fundamental aspect of computer graphics that has been the focus of extensive research for decades. Recent advancements in neural representations, generative modelling and differentiable rendering techniques have propelled this field of content generation forward. As a result, computational systems that can convert simple user inputs like texts into image, text/images into videos/3D shapes have gained significant attention, empowering non-expert users to easily create visual content directly from such inputs. In this course, we will cover the fundamentals of neural representations for images, video and 3D content and generative modelling for image, video and 3D generation under different training paradigms e.g., paired 3D data, unpaired 3D data, without 3D data. .

• Instructor: Dr. Lokender Tiwari
• Coordinator: Prof. Chetan Arora
• Lecture Timings: Wednesdays 3:30 PM to 5:00 PM, Fridays 5:00PM to 6:30 PM
• Lecture Venue: LHC 521

This is a tentative schedule for the course. Please check for updates regularly.

(9 Lectures, 1.5 hrs each, 13.5 hours total).

• Lecture 1: Genarative Adversarial Network (GAN) [PDF]
• Lecture 2: StyleGAN and Normalizing Flows [PDF]
• Lecture 3: Variational Autoencoder (VAE & VQVAE) [PDF]
• Lecture 4: Score Based Diffusion Model [PDF]
• Lecture 5: DDPM and DDIM
• Lecture 6: Text to Image Generation
• Lecture 7: Text to Video Generation
• Lecture 8: 3D Generation - Part 1, (3D Representations : Voxel, Point Cloud, Meshes, Triplane, Implicit Surfaces, 3D Gaussian, DMTET, Structured Representation)
• Lecture 9: 3D Generation - Part 2, (Approaches focused on paired, unpaired and no GT 3D training data. e.g., SDFusion, SHAP-E , DreamFusion, Magic3D, ProlificDreamer, Point-E, Wonder3D)

• Instructor: Dr. Lokender Tiwari - lokender.work@gmail.com
• Coordinator: Prof. Chetan Arora - chetan@cse.iitd.ac.in