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 IDARS-5.7
Paper Title SEGMENTATION-AWARE TEXT-GUIDED IMAGE MANIPULATION
Authors Tomoki Haruyama, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama, Hokkaido University, Japan
SessionARS-5: Image and Video Synthesis, Rendering and Visualization
LocationArea I
Session Time:Tuesday, 21 September, 08:00 - 09:30
Presentation Time:Tuesday, 21 September, 08:00 - 09:30
Presentation Poster
Topic Image and Video Analysis, Synthesis, and Retrieval: Image & Video Synthesis, Rendering, and Visualization
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract We propose a novel approach that improves text-guided image manipulation performance in this paper. Text-guided image manipulation aims at modifying some parts of an input image in accordance with the user's text description by semantically associating the regions of the image with the text description. We tackle the conventional methods' problem of modifying undesired parts caused by differences in representation ability between text descriptions and images. Humans tend to pay attention primarily to objects corresponding to the foreground of images, and text descriptions by humans mostly represent the foreground. Therefore, it is necessary to introduce not only a foreground-aware bias based on text descriptions but also a background-aware bias that the text descriptions do not represent. We introduce an image segmentation network into the generative adversarial network for image manipulation to solve the above problem. Comparative experiments with three state-of-the-art methods show the effectiveness of our method quantitatively and qualitatively.