Jack Defay will present his MSE talk “Synthetic Data Generation for 6DOF Object Rearrangement” Monday, April 22 at 3:00 PM in CS 105. Advisor: Jia Deng; Reader: Olga Russakovsky Abstract: State of the art methods for object rearrangement tasks will need better labeled, and fuller distributions of, data to train on. Many difficult object classes, like shiny or transparent objects, are important for deployment scenarios like a kitchen. Furthermore, challenges to labeling, like occlusions, are essential for a model to be able to handle in more complex or cluttered environments. We approach these challenges in a few ways: improved data collection techniques, semi-automatic data labeling pipelines, and synthetic data generation. We believe that synthetic data will continue to close the sim to real gap, and due to its better coverage of the underlying distribution and perfect labels, will become a more cost effective solution to training complex vision problems like 6DOF object rearrangement. This paper focuses on techniques for synthetic data generation for the object rearrangement task as well as methods to improve the real world data collection pipeline for benchmarking the synthetic datasets. CS Grad Calendar: [ https://calendar.google.com/calendar/event?action=TEMPLATE&tmeid=MW1yc2FwZHBrZmxmMWZzbXMycnF2NmZqaDcgYWNnMDc5YmxzbzRtczNza2tmZThwa2lyb2dAZw&tmsrc=acg079blso4ms3skkfe8pkirog%40group.calendar.google.com | https://calendar.google.com/calendar/event?action=TEMPLATE&tmeid=MW1yc2FwZHBrZmxmMWZzbXMycnF2NmZqaDcgYWNnMDc5YmxzbzRtczNza2tmZThwa2lyb2dAZw&tmsrc=acg079blso4ms3skkfe8pkirog%40group.calendar.google.com ]