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  1. openaccess.thecvf.com

    In this work, our aim is to introduce a large annotated dataset for detecting manipulated visual content. Inspired by the semi-automatic way that ImageNet has been built, we will build in a semi-automatic way a dataset that cap-tures a large diversity of image and manipulation artifacts. Creating such a dataset is a challenging task. Each camera
  2. ieeexplore.ieee.org

    IMD2020: A Large-Scale Annotated Dataset Tailored for Detecting Manipulated Images Abstract: Witnessing impressive results of deep nets in a number of computer vision problems, the image forensic community has begun to utilize them in the challenging domain of detecting manipulated visual content. One of the obstacles to replicate the success ...
    Author:Adam Novozamsky, Babak Mahdian, Stanislav SaicPublished:2020
  3. staff.utia.cas.cz

    IMD2020: A Large-Scale Annotated Dataset Tailored for Detecting Manipulated Images. Description & Download. IMD2020 Real-Life Manipulated Images. This dataset contains 2,010 real-life manipulated images downloaded from the Internet. Corresponding real versions of these images are also provided. Moreover, there is a manually created binary mask ...
  4. openaccess.thecvf.com

    Moreover, we also created the same number of digitally manipulated images by using a large variety of core image manipulation methods as well we advanced ones such as GAN or Inpainting resulting in a dataset of 70,000 images. In addition to this dataset, we also created a dataset of 2,000 "real-life" (uncontrolled) manipulated images.
    Author:Adam Novozamsky, Babak Mahdian, Stanislav SaicPublished:2020
  5. ietresearch.onlinelibrary.wiley.com

    the difficultproblem of detecting manipulated imagery. But, we face a few obstacles while achieving this objective. A major obstacle is that deep nets require large‐scale datasets for training. For image classification,the ImageNet [2] released in 2009, yielded a large‐scale annotated dataset containing 1,000 distinct object categories.
  6. asep.lib.cas.cz

    IMD2020: A Large-Scale Annotated Dataset Tailored for Detecting Manipulated Images. 2020 IEEE Winter Applications of Computer Vision Workshops (WACVW). Piscataway: IEEE, 2020, s. 71-80. ISBN 978-1-7281-7162-3. [2020 Winter Conference on Applications of Computer Vision (WACV '20). Snowmass Village, CO (US), 01.03.2020-05.03.2020]
  7. researchgate.net

    Training includes CASIA v2 [17], FantasticReality [26], IMD2020 [37] and a dataset of manipulated images created by [27] by applying splicing and copy-move using either COCO [30] training set or ...
  8. mendeley.com

    Here, the authors introduce three datasets. First, we identified the majority of camera models on the market. Then, we collected a dataset of 35,000 real images captured by these cameras. We also created the same number of digitally manipulated images. Additionally, we also collected a dataset of 2,000 'real-life' (uncontrolled) manipulated ...
  9. digital-library.theiet.org

    Extended IMD2020: a large‐scale annotated dataset tailored for detecting manipulated images. ... Mahdian, B., Saic, S.: Imd2020: Imd2020: A large‐scale annotated dataset tailored for detecting manipulated images. In: Proceedings of the IEEE/CVF Winter Conference on Applications of computer Vision (WACV) Workshops, pp. 71-80. IEEE ...
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