Zeyu Wang (ECE) will present his Pre FPO "Tackling Imperfections in Data for Real-world Vision Systems" on Tuesday, February 8, 2022 at 3pm via Zoom Zoom link: https://princeton.zoom.us/j/8491812031 Committee members: Prof. Olga Russakovsky (advisor), Prof. Karthik Narasimhan, Prof. Jia Deng, Prof. Peter Ramadge (ECE). Title: Tackling Imperfections in Data for Real-world Vision Systems Abstract: Data is the fuel of modern neural networks and largely contributes to the rise of deep learning. However, ‘no dataset is perfect’ and various data issues pose significant challenges for building real-world vision systems. In this talk, I will present our works on tackling three prevalent data issues: spurious correlation, long-tail and noise. First, I will introduce a new benchmark for studying how to mitigate bias learned from spurious correlation in data. Then I will talk about a new metric and an inference-time re-ranking technique for tackling long-tail data problems in captioning models. Finally, I will discuss how to utilize multi-query to address data noise for video retrieval systems.