Some material from Visual Appearance Representations for Rendering file:///Users/ravir/6160/index.html Sampling and Reconstruction of Visual Appearance Week 1: Intro, Basic Prelims, BRDFs and Radiometry Week 2: MC Rendering (path tracing), Taxonomy of Appearance Representations Week 3: Applications (Comp Photo, Light Transport, PRT??, IBR??, Light Fields, Sampling and Reconstruction) [Maybe some paper presentations here] Week 4: Basics on Denoising and Frequency Analysis Presentation of Basic A-Priori and A-Posteriori papers Week 5: Continue basic denoising papers Week 6: Brief lecture on feature spaces, practice in industry Presentations of feature-based, real-time methods Week 7: Compressive sensing, matrix completion? Presentations of light transport acquisition papers Week 8: Imaging challenges and deep learning Presentations of papers on sparse interpolation in imaging (or skip this and just have Nima present on rendering and imaging?) Week 9: Latest papers, miscellaneous Conclusion/wrap up Week 10: Project Presentations Immediate Tasks: - 1. Details below. [DONE] - 2. Create Basic Website with Prelim Papers. - 3. Lectures start making (really need to have all the lectures to fin. papers) - 4. Iterate regarding papers ------------------------------- Details: (Need to design lectures for weeks 1 to 4 to see if we need papers presented) (need to ack up front that much is my own work) Week 1. Intro, Basic Prelims, BRDFs and Radiometry [Need to design nice intro lecture] - From file:///Users/ravir/6160/index.html - Eurographics STAR report M.F. Cohen and J.R. Wallace, 1993. Radiosity and Realistic Image Synthesis, Chapter 2 by Pat Hanrahan. Rendering Concepts [handed out in class; not available online] H. Jensen, 2001. Realistic Image Synthesis using Photon Mapping, Chapter 2: Fundamentals of Global Illumination [handed out in class; not available online] Scribed lecture notes on overview of appearance models and BRDFs from Stanford. Overview and BRDFs - Basics of Radiometry (from CS 283) - Maybe include taxonomy of appearance representations part from file:///Users/ravir/6160/index.html Week 2. Monte Carlo Rendering - Reflection and Rendering Equation (shorten, from CSE 163) - Monte Carlo Integration (from CS 283, shorten). - Path Tracing Lecture (from CS 283 at Berkeley, shorten) [Include some rendering optimizations like irradiance caching?] [See Feb 14,19,21,26 lectures https://inst.eecs.berkeley.edu/~cs283/sp13/] - See earlier work. Siggraph Course notes (recent) - Rendering Equation - Cook 84 - Recent siggraph course notes on path tracing revolution Week 3, Applications - New lecture, subsets of past lectures. Brief look on light fields, computational photography (from CSE 163), Light Transport Acquisition (jobtalk pieter peers slides), and brief lecture on PRT? - Light Field papers - Plenoptic Cameras - Search for a good light transport paper (Debevec 2000?) - PRT paper Week 4 lecture, Basics of Denoising and Frequency Analysis [I need to work on this lecture, but a lot is frequency analysis from previous]. - Mitchell 87, 91, Guo 98? (other more recent ones?) [discuss these in text] - Chai et al. 2000 - Durand et al. 2005 for reading - Overbeck et al. 2009 (Discuss Overveck 2009 in some detail, at least breifly?) Presentations: Hachisuka et al. 2008 Overbeck et al. 2009 Egan et al. 2009 Week 5 paper presentations on basic denoising papers: [Brief presentation (by me?) of DoF, MB, SS, GI, EuroGraphics STAR report?] - Eurographics STAR report (not presented) - Soler 2009 - Egan 2011 - Belcour 2013 Covariance tracing - Lehtinen 2011 light field reconstruction? - Rousselle 2012? RKZ12 NL-means filter - Munkberg 2014? (see STAR MVH*14, real-time filters for motion blur/dof) (1 of these 2) Week 6 Brief discussion of feature spaces, practice in industry, Real-Time [Need to have brief lecture on these topics] Feature-Based Denoising (2.3 of STAR report) - Sen and Darabi 2012 - Rousselle 2013 - Moon 2015 (2016? Adaptive polynomial Rendering) (Might need to say a few words about real-time, put in context) Real-Time: - Mehta 2012 - Yan 2015 - MAAF (Lifan 2017) Week 7 Lecture on compressive sensing, matrix completion, including Pieter Peers paper (I will need to prepare this lecture, is it enough for full lec.?) I could also talk about compressive structured light [May be full lecture, if time permits paper presentations Peers et al. 09, Gu et al. 08, Adaptive Matrix Column Sampling and Completion for Rendering Participating Media SIGGRAPH Asia 2016 (maybe only present this one) More light transport acquisition papers: - Kernel Nystrom Method for Light Transport (SIGGRAPH Asia 2009) - O'Toole et al. 2010 Optical Computing for Fast Light Transport Analysis - Two Shot Reflectance Acquisition (Zexiang SIGGRAPH Asia 2016) Week 8 [Brief Lecture on Problems in Imaging, Sparse Interpolation] Presentation of papers on sparse interpolation for imaging - Marwah et al. 2013 Compressive Light field Photography - Wetsztein et al. Compressive Light Field Displays - Image Based Relighting Using Neural Networks (Ren et al. SIGGRAPH 2015) [Nima Lecture on deep learning for rendering and imaging] [Kalantari et al. 2015 Kalantari et al. 2016 Light field interpolation ] Week 9 [Brief Lecture concluding course and wrapping up, Summary] (maybe something on learning) - Siggraph 2017 Bako et al. learning paper - Siggraph 2017 Chaitanya et al. learning paper - [Maybe] Spatiotemporal variance guided filtering Schied et al. HPG 17 Best P. [Hold 1 day free for visit day etc.] (Back up lecture is on light fields from l4cv) Week 10 Student presentations of projects, may skip final lecture if one enough [May be only 20 papers to be presented by students, more lecture-heavy course, better per feedback, but work on lectures. 1 per student]