Advanced Lecture Series in Pattern Recognition
题 目 (TITLE)：Recent Results on Semantic and Video Segmentation
讲 座 人 (SPEAKER)：Prof. Ming-Hsuan Yang (UC Merced / Google Cloud)
主 持 人 (CHAIR)： Dr. Tianzhu Zhang
时 间 (TIME)：15:00pm, April 10 (Tuesday), 2018
地 点 (VENUE)：No.1 Conference Room (3rd floor), Intelligence Building
报告摘要（ABSTRACT）：Convolutional neural network-based approaches for semantic segmentation rely on supervision with pixel-level ground truth but may not generalize well to unseen image domains. As the labeling process is tedious and labor intensive, developing algorithms that can adapt source ground truth labels to the target domain is of great interest. In the first part of this talk, I will present an adversarial learning method for domain adaptation in the context of semantic segmentation. Considering semantic segmentations as structured outputs that contain spatial similarities between the source and target domains, we adopt adversarial learning in the output space. Extensive experiments show that the proposed method performs favorably against the state-of-the-art methods. In the second part of this talk, I will present a fast and accurate video object segmentation algorithm that can immediately start the segmentation process once receiving the images. We utilize a part-based tracking method to deal with challenging factors such as large deformation, occlusion, and cluttered background. Our method performs favorably against state-of-the-art algorithms in terms of accuracy on the DAVIS benchmark dataset, while achieving much faster runtime performance.
报告人简介（BIOGRAPHY）：Ming-Hsuan Yang is a professor in Electrical Engineering and Computer Science at University of California, Merced. He received the PhD degree in Computer Science from the University of Illinois at Urbana-Champaign in 2000. He serves as an area chair for several conferences including CVPR, ICCV, ECCV, ACCV, AAAI, and FG. He serves as a program co-chair for IEEE International Conference on Computer Vision in 2019 as well as Asian Conference on Computer Vision in 2014, and general co-chair for Asian Conference on Computer Vision in 2016. He serves as an associate editor of the IEEE Transactions on Pattern Analysis and Machine Intelligence (2007 to 2011), International Journal of Computer Vision, Computer Vision and Image Understanding, Image and Vision Computing, and Journal of Artificial Intelligence Research. Yang received the Google faculty award in 2009, and the Distinguished Early Career Research award from the UC Merced senate in 2011, the Faculty Early Career Development (CAREER) award from the National Science Foundation in 2012, and the Distinguished Research Award from UC Merced Senate in 2015.