Lecture 4: Latent Diffusion Models and latest architectures

Lecture 3: Denoising Diffusion Probabilistic Models

Lecture 2: Variational AutoEncoders

Lecture 1 - CSE 555: Essence of Generative AI

Invited Guest Lecture - CSE 555 Pattern Recognition - Spring 2025

Prompt Inversion using Diffusion LLMs

Lectures 15,16,17: Diffusion Models

Oral Qualifying Exam - Naresh

My PhD Oral Qualifying Exam slides

Lectures 13,14 : AutoEncoders, VAEs, CVAEs, GANs, CGANs

Lecture 12: Intro to GenAI: Data Distribution

Lecture 10,11: Learning-based (Data driven) Computer Vision with Neural Networks

Lecture 9: Feature Detection and Extraction

Lectures 6,7,8: Stereo Vision and Depth Estimation

Lecture 5: Image Processing (Fourier Domain)

Lecture 4: Image Processing (Image Transformations)

Lectures 2,3 : Image Formation and the Pinhole Camera

Lecture 1: What is an Image?

naresh-ub.github.io/cvip/lectures/lecture-1.html

Convolutional Neural Networks

Invited Guest Lecture - CSE 573 CVIP - Spring 2025

Lecture 0: Course Logistics and Syllabus

naresh-ub.github.io/cvip-summer25/syllabus.html

Unlearnable Samples in Diffusion Models

Work accepted at ACM MM 2025 🎉

Your Text Encoder can be an Object-Level Watermarking Controller

Work accepted at ICCV 2025 🎉