南京大学计算机软件新技术国家重点实验室

摘 要：

Deep convolutional features have now been widely applied to image retrieval and demonstrated excellent performance. Given an image database, the deep features of images are usually extracted by the model pre-trained on a large-scale benchmark dataset and used for retrieval. Nevertheless, the image database on which the retrieval is conducted could be from a domain different from that of the benchmark dataset. How to adapt these pre-trained deep features to a given image database becomes an issue. In particular, the unsupervised nature of image retrieval makes this issue challenging. 

This talk will report our recent work on addressing the above issue through utilising diffusion process. By considering the underlying distribution of the images in a database, diffusion process can better evaluate image similarity and improve retrieval. We propose to treat diffusion process as a “black box” and directly model it by deep neural networks, so as to obtain the image representation that assimilates the effect of diffusion process and are therefore better adapted to the given image database. The proposed approach is fully unsupervised in the sense that it needs neither image labels nor external datasets. The adapted deep features directly work with Euclidean search and completely avoids online diffusion process in retrieval. Via experimental study, we will show its effectiveness and investigate its appealing characteristics such as the generalisation to new image insertion. Also, the potential extension to this work will be discussed.

报告人简介:

Lei Wang received his PhD degree from Nanyang Technological University, Singapore. He is now Associate Professor at School of Computing and Information Technology of University of Wollongong, Australia. His research interests include machine learning, pattern recognition, and computer vision. Lei Wang has published 150+ peer-reviewed papers, including those in highly regarded journals and conferences such as IEEE TPAMI, IJCV, CVPR, ICCV and ECCV, etc. He was awarded the Early Career Researcher Award by Australian Academy of Science and Australian Research Council. He served as the General Co-Chair of DICTA 2014, Program Co-Chair of VCIP2019, Area Chair of ICIP2019, and on the Technical Program Committees of 20+ international conferences and workshops. Lei Wang is senior member of IEEE.

时间：9月30日  10:00-11:00

地点：计算机科学技术楼230室