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You are reading the documentation for MMEditing 0.x, which will soon be deprecated by the end of 2022. We recommend you upgrade to MMEditing 1.0 to enjoy fruitful new features and better performance brought by OpenMMLab 2.0. Check out the changelog, code and documentation of MMEditing 1.0 for more details.

Overview

  • Number of papers: 11

    • DATASET: 11

For supported editing algorithms, see modelzoo overview.

Generation Datasets

  • Number of papers: 2

    • [DATASET] Image-to-Image Translation With Conditional Adversarial Networks ( Paired Dataset for Pix2pix ⇨)

    • [DATASET] Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks ( Unpaired Dataset for CycleGAN ⇨)

Inpainting Datasets

  • Number of papers: 3

    • [DATASET] Context Encoders: Feature Learning by Inpainting ( Paris Street View Dataset ⇨)

    • [DATASET] Places: A 10 Million Image Database for Scene Recognition ( Places365 Dataset ⇨)

    • [DATASET] Progressive Growing of Gans for Improved Quality, Stability, and Variation ( CelebA-HQ Dataset ⇨)

Matting Datasets

  • Number of papers: 1

    • [DATASET] Deep Image Matting ( Composition-1k Dataset ⇨)

Super-Resolution Datasets

  • Number of papers: 5

    • [DATASET] Ntire 2017 Challenge on Single Image Super-Resolution: Dataset and Study ( DIV2K Dataset ⇨)

    • [DATASET] Ntire 2019 Challenge on Video Deblurring and Super-Resolution: Dataset and Study ( REDS Dataset ⇨)

    • [DATASET] On Bayesian Adaptive Video Super Resolution ( Vid4 Dataset ⇨)

    • [DATASET] Real-Esrgan: Training Real-World Blind Super-Resolution With Pure Synthetic Data ( DF2K_OST Dataset ⇨)

    • [DATASET] Video Enhancement With Task-Oriented Flow ( Vimeo90K Dataset ⇨)

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