Johan Ospina will present his MSE Talk and Thesis "Crowdflow - creating a crowdsourced optical flow dataset" on Tuesday, April 20, 2021 at 3:30PM via Zoom. Zoom Link: https://princeton.zoom.us/j/6951559457 https://princeton.zoom.us/j/6951559457 Committee Members: Jia Deng (adviser) and Olga Russakovsky (reader) All are welcome to attend. Title: Crowdflow - creating a crowdsourced optical flow dataset. Abstract: Datasets for training Deep Learning solutions for Optical Flow have been for the most part created in synthetic rendering environments or in highly structured real life environments without much variance of environment. While CGI methods are able to produce accurate training data for learning algorithms, they are limited to either the quality of the rendering algorithms used or the variation of the library of 3D models they have access to. On the other end of the spectrum, the real life datasets that exist are limited in the types of environments they can image. Crowdflow aims to bring a crowdsourced dataset of sparse Optical Flow annotations in a wide variety of real life environments in order to measure how well current state of the art methods perform on a variety of real life scenes.