SenroDR - A New Differentiable Rendering Framework

Abstract

Rendering is the process of converting digital information into image or video media Due to the discontinuity of the scene rendering has long been considered impossible to differentiate Differetiable rendering(DR) is a relatively new topic in computer graphics It’s unbiased solution was found in the year 2018 by Lee [1] There are two existing general-purpose DR in the world and some special-purpose or toy DR available However None of them meet our need We need a more efficient in both speed and memory consumption and flexible DR for research Thus here we present our new differentiable renderer SenroDR In thesis we briefly introduce and break down our SenroDR framework Our other contribution is mathematical derivation of curve sampling which is extended from edge sampling technique developed by Lee [1] And we designed several different experiments based on the contribution of the paper

Date of Award	2020
Original language	English
Supervisor	Wei-Ta Chu (Supervisor)