2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information
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Paper Detail

Paper IDIVMSP-21.1
Paper Title JOINT LEARNING OF IMAGE AESTHETIC QUALITY ASSESSMENT AND SEMANTIC RECOGNITION BASED ON FEATURE ENHANCEMENT
Authors Xiangfei Liu, Shandong University, China; Xiushan Nie, Shandong Jianzhu University, China; Zhen Shen, Yilong Yin, Shandong University, China
SessionIVMSP-21: Image & Video Quality
LocationGather.Town
Session Time:Thursday, 10 June, 14:00 - 14:45
Presentation Time:Thursday, 10 June, 14:00 - 14:45
Presentation Poster
Topic Image, Video, and Multidimensional Signal Processing: [IVSMR] Image & Video Sensing, Modeling, and Representation
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract Aesthetic quality assessment and semantic recognition are the two fundamental aspects of image perception and understanding tasks. Though these two tasks are related, most of the current research generally treats them as independent problems without any interaction. In this paper, we explore the relationships between aesthetic quality assessment and semantic recognition task, and employ a multi-task convolutional neural network with feature enhancement mechanism to effectively integrate these two tasks. A novel Enhanced Aggregation of Features Network (EAFNet) for joint learning of the two tasks is proposed to enhance the valid features and suppress the invalid features of each task in both channel and spatial dimensions. Experiments conducted on two benchmark datasets well verify the superior performance of EAFNet in handling aesthetic quality assessment and semantic recognition tasks.