2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

Imaging Without Borders

2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

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Paper Detail

Paper IDSMR-3.3
Paper Title EDGE-AWARE SUPERPIXEL SEGMENTATION WITH UNSUPERVISED CONVOLUTIONAL NEURAL NETWORKS
Authors Yue Yu, Yang Yang, Kezhao Liu, Xi'an Jiaotong University, China
SessionSMR-3: Image and Video Representation
LocationArea F
Session Time:Tuesday, 21 September, 15:30 - 17:00
Presentation Time:Tuesday, 21 September, 15:30 - 17:00
Presentation Poster
Topic Image and Video Sensing, Modeling, and Representation: Image & video representation
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract Superpixels provide an efficient representation of images, and are applicable for subsequent vision tasks. In this paper, we propose an edge-aware superpixel algorithm based on an unsupervised convolutional neural network (CNN). Noticing that to adhere the boundaries of objects is one of the most essential characteristics of superpixels, we propose an entropy-based edge-aware term, which helps fit the differential model of the pixel-superpixel soft-assignment matrix predicted from CNN to image gradients, i.e. generate boundary-aligning superpixels. The proposed algorithm yields more boundary-adhering superpixels, and experimental results on BSDS500 show the effectiveness of the proposed edge-aware term.