Rendering of complex scenes from software such as Blender is time consuming, but corresponding auxiliary data such as depth or object segmentation maps are relatively fast to generate. The auxiliary data also provides a wealth of information for tasks such as optical flow prediction. In this paper we present the QuickRender dataset, a collection of procedurally generated scenes rendered into over 5,000 sequential image triplets along with accompanying auxiliary data. The goal of this dataset is to provide a diversity of scenes and motion while maintaining realistic behaviours. A sample application using this dataset to perform single image super resolution is also presented. The dataset and related source code can be found at https://github.com/MP-mtroyal/MetaSRGAN.

Sewing patterns are a form of technical document, requiring expertise to author and understand. Digital patterns are typically produced and sold as PDFs with human-interpretable vector graphics, but there is little consistency or machine-readable metadata in these documents. A custom file format would enable digital pattern manipulation tools to enhance or replace a paper based workflow.

Print-at-home PDF sewing patterns have gained popularity over the last decade and now represent a significant proportion of the home sewing pattern market. Recently, an all-digital workflow has emerged through the use of ceiling-mounted projectors, allowing for patterns to be projected directly onto fabric. However, PDF patterns produced for printing are not suitable for projecting.

The portable document format (PDF) is both versatile and complex, with a specification exceeding well over a thousand pages. For independent developers writing software that reads, displays, or transforms PDFs, it is difficult to comprehensively account for all of the potential variations that might exist in the wild. Compounding this problem are the usage agreements that often accompany purchased and proprietary PDFs, preventing end users from uploading a troublesome document as part of a bug report and limiting the set of test cases that can be made public for open source development.