PPT-Generative Models of Images of Objects

S M Ali Eslami Joint work with Chris Williams Nicolas Heess John Winn June 2012 UoC TTI Classification Localization ForegroundBackground Segmentation Partsbased Object Segmentation Segment this. Chen-Ping Yu. Prof. Dimitris Samaras. Prof. Greg . Zelinsky. Introduction. The goal: model human visual clutter perception.. Visual clutter: A “confused collection”, or a “crowded disorderly state”. Increasing visual clutter.. Authors. : Desmond Elliot & Arjen P. de . Vries. Presentation of Paper by . : Jantre Sanket R. (12309), . Senior Undergraduate Student, . CSE, IIT Kanpur. Abstract. Visual Dependency Representation(VDR): . Chen-Ping Yu. Prof. Dimitris Samaras. Prof. Greg . Zelinsky. Introduction. The goal: model human visual clutter perception.. Visual clutter: A “confused collection”, or a “crowded disorderly state”. Increasing visual clutter.. Part-based models. Many slides adapted from Fei-Fei Li, Rob Fergus, and Antonio Torralba. Implicit shape models. Visual codebook is used to index votes for object position. B. Leibe, A. Leonardis, and B. Schiele, . vs. Discriminative models. Roughly:. Discriminative. Feedforw. ard. Bottom-up. Generative. Feedforward recurrent feedback. Bottom-up horizontal top-down. Compositional . generative models require a flexible, “universal,” representation format for relationships.. Nets. İlke Çuğu 1881739. NIPS 2014 . Ian. . Goodfellow. et al.. At a . glance. (. http://www.kdnuggets.com/2017/01/generative-adversarial-networks-hot-topic-machine-learning.html. ). Idea. . Behind. Models. Models We Will Use. Wiring diagrams for Chemical Reactions. Mathematical Models (Differential Equations). Computer Models . (. RuleBender. ). What good are models?. Models are abstract descriptions of the world.. Carilion. Research Institute. Bradley Department of Electrical & Computer Engineering. Department of Psychiatry and . Behavioral. Medicine, VTC School of Medicine. Dynamic Causal . Modelling. . Akrit Mohapatra. ECE Department, Virginia Tech. What are GANs?. System of . two neural networks competing against each other in a zero-sum game framework. . They were first introduced by . Ian Goodfellow. An Overview. Yidong. Chai. 1,2. , . Weifeng Li. 1,3. , Hsinchun Chen. 1. 1 . Artificial Intelligence Laboratory, The University of Arizona. 2 . Tsinghua University. 3 . University of Georgia. 1. Acknowledgements. ). Prof. . Ralucca Gera, . Applied Mathematics Dept.. Naval Postgraduate School. Monterey, California. rgera@nps.edu. Excellence Through Knowledge. Learning Outcomes. I. dentify . network models and explain their structures. Machine Learning/Computer Vision. Alan Yuille. UCLA: Dept. Statistics. Joint App. Computer Science, Psychiatry, Psychology. Dept. . Brain and Cognitive Engineering, Korea University. Structure of Talk. Nisheeth. Coin toss example. Say you toss a coin N times. You want to figure out its bias. Bayesian approach. Find the generative model. Each toss ~ Bern(. θ. ). θ. ~ Beta(. α. ,. β. ). Draw the generative model in plate notation. Fall 2023. What is Generative AI?. ChatGPT, Bing, Bard, . DallE. …. Generative AI, like ChatGPT, uses machine learning to create new content. While generative AI tools can help explore new ideas, write text, and get feedback, there are important limitations to these tools to keep in mind..