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  1. High Dynamic Range (HDR) imaging with modulo cam-eras involves solving a challenging inverse problem, where degradation occurs due to the modulo operation applied to the target HDR …

  2. Zhao et al. [58] used a modulo camera that is able to wrap the high radiance of dynamic range scene pe-riodically and save modulo information, then used Markov Random Field to unwrap …

  3. WACV 2022 Open Access Repository

    Positional learning trains the model to learn the modulo-2 position of pixels, leveraging the translation-invariance of CNN to replicate the underlying mosaic and its potential inconsistencies.

  4. We evaluate our DUN, PnP-UA and UnModNet which are specifically designed for modulo HDR reconstruction, on the sample of real-sensor dataset [2]. This dataset collects 8-bit grayscale …

  5. Without additional illumination modules, passive 3D imaging systems exploit unconven-tional sensors for HDR imaging, such as single-photon avalanche diodes [17], quanta image sensors …

  6. CVPR 2020 Open Access Repository

    To this aim we designed a CNN structure inspired from demosaicing algorithms and directed at classifying image blocks by their position in the image modulo (2 x 2).

  7. Mod-Squad: Designing Mixtures of Experts As Modular Multi-Task Learners Zitian Chen1, Yikang Shen2, Mingyu Ding3, Zhenfang Chen2, Hengshuang Zhao3, Erik Learned-Miller1, Chuang …

  8. Positional learning trains the model to learn the modulo-2 position of pixels, leveraging the translation-invariance of CNN to replicate the underlying mosaic and its potential inconsistencies.

  9. This paper describes an approach to visual question an-swering based on a new model architecture that we call a neural module network (NMN). This architecture makes it possible …

  10. To this aim we designed a CNN structure inspired from demosaicing algorithms and directed at classifying image blocks by their position in the image modulo (2 × 2).