Training Data Optimization in Human-Centric Analysis
Liang Zheng · 2023
Training data are a pillar in computer vision applications. While existing works typically assume fixed training sets, I will discuss how training data optimization complements and benefis state-of-the-art computer vision models. In particular, this talk focuses on a few human-centric applications: person re-identification, multi-object tracking , and micro-expression recognition. For person re-identification, I will discuss how to search for training data that match the target domain distribution. For tracking, I will introduce our research utilizing synthetic human data to learn association policies. Finally, I will introduce a protocol to synthesize large amounts of micro-expression training images leading to a state-of-the-art recognition system. I conclude the talk with trends and new problems in data-centric computer vision.