國立清華大學資訊工程學系

Department of Computer Science

National Tsing Hua University

專題演講

SEMINAR

主講人：Tsung-Yu Lin (林宗昱)

SPEAKER University of Massachusetts, Amherst, USA

題　目：Bilinear CNN Models for Visual Recognition

TOPIC  

時  間： 106年01月13日(五)11:00AM - 12:00AM

DATE　　

地　點： 台達館614室

PLACE

                         聯絡人：賴尚宏教授

Abstract
The recent success in visual recognition using deep neural network has stimulated the research in exploring new network architectures. Building feature encoders on top of convolutional features is a popular approach for this goal. I will introduce the bilinear CNNs, an architecture that efficiently represents an image as a pooled outer product of two CNN features, and its applications on fine-grained classification and texture recognition. The talk will: (1) introduce a general formulation of bilinear model for classification, (2) derive a family of end-to-end trainable bilinear models that generalize classical image representations, (3) discuss the dimensionality reduction techniques on bilinear models, (4) evaluate the performance on fine-grained recognition and texture recognition tasks, and (5) visualize the attributes learned by the models. The source code for the complete system is available at  http://vis-www.cs.umass.edu/bcnn