Update computational-imaging.md

sections/computational-imaging.md

@@ -31,7 +31,7 @@
 | The Differentiable Lens: Compound Lens Search Over Glass Surfaces and Materials for Object Detection | [![WEB Page](https://img.shields.io/badge/WEB-Page-159957.svg)](https://light.princeton.edu/publication/joint-lens-design/) <br /> [![GitHub](https://img.shields.io/github/stars/princeton-computational-imaging/joint-lens-design)](https://github.com/princeton-computational-imaging/joint-lens-design) | [![thecvf](https://img.shields.io/badge/pdf-thecvf-7395C5.svg)](https://openaccess.thecvf.com//content/CVPR2023/papers/Cote_The_Differentiable_Lens_Compound_Lens_Search_Over_Glass_Surfaces_and_CVPR_2023_paper.pdf) <br /> [![arXiv](https://img.shields.io/badge/arXiv-2212.04441-b31b1b.svg)](https://arxiv.org/abs/2212.04441) | [![YouTube](https://img.shields.io/badge/YouTube-%23FF0000.svg?style=for-the-badge&logo=YouTube&logoColor=white)](https://www.youtube.com/watch?v=f6NuKnPwVDc) |
 | Megahertz Light Steering without Moving Parts | [![WEB Page](https://img.shields.io/badge/WEB-Page-159957.svg)](https://imaging.cs.cmu.edu/ultrafast_steering/#code) | [![thecvf](https://img.shields.io/badge/pdf-thecvf-7395C5.svg)](https://openaccess.thecvf.com//content/CVPR2023/papers/Pediredla_Megahertz_Light_Steering_Without_Moving_Parts_CVPR_2023_paper.pdf) | [![YouTube](https://img.shields.io/badge/YouTube-%23FF0000.svg?style=for-the-badge&logo=YouTube&logoColor=white)](https://www.youtube.com/watch?v=hD8btaKr5Bc) |
 | Text2Scene: Text-Driven Indoor Scene Stylization with Part-Aware Details <br /> ![CVPR - Highlight](https://img.shields.io/badge/CVPR-Highlight-FFFF00) | :heavy_minus_sign: | [![thecvf](https://img.shields.io/badge/pdf-thecvf-7395C5.svg)](https://openaccess.thecvf.com//content/CVPR2023/papers/Hwang_Text2Scene_Text-Driven_Indoor_Scene_Stylization_With_Part-Aware_Details_CVPR_2023_paper.pdf) <br /> [![arXiv](https://img.shields.io/badge/arXiv-2308.16880-b31b1b.svg)](https://arxiv.org/abs/2308.16880) | [![YouTube](https://img.shields.io/badge/YouTube-%23FF0000.svg?style=for-the-badge&logo=YouTube&logoColor=white)](https://www.youtube.com/watch?v=CGIXY2kwIYM) |
-| RankMix: Data Augmentation for Weakly Supervised Learning of Classifying Whole Slide Images with Diverse Sizes and Imbalanced Categories | :heavy_minus_sign: | [![thecvf](https://img.shields.io/badge/pdf-thecvf-7395C5.svg)](https://openaccess.thecvf.com//content/CVPR2023/papers/Chen_RankMix_Data_Augmentation_for_Weakly_Supervised_Learning_of_Classifying_Whole_CVPR_2023_paper.pdf) | :heavy_minus_sign: |
+| RankMix: Data Augmentation for Weakly Supervised Learning of Classifying Whole Slide Images with Diverse Sizes and Imbalanced Categories | [![GitHub](https://img.shields.io/github/stars/willpower057/RankMix)](https://github.com/willpower057/RankMix) | [![thecvf](https://img.shields.io/badge/pdf-thecvf-7395C5.svg)](https://openaccess.thecvf.com//content/CVPR2023/papers/Chen_RankMix_Data_Augmentation_for_Weakly_Supervised_Learning_of_Classifying_Whole_CVPR_2023_paper.pdf) | :heavy_minus_sign: |
 | Guided Depth Super-Resolution by Deep Anisotropic Diffusion | [![GitHub](https://img.shields.io/github/stars/prs-eth/Diffusion-Super-Resolution)](https://github.com/prs-eth/Diffusion-Super-Resolution) | [![thecvf](https://img.shields.io/badge/pdf-thecvf-7395C5.svg)](https://openaccess.thecvf.com//content/CVPR2023/papers/Metzger_Guided_Depth_Super-Resolution_by_Deep_Anisotropic_Diffusion_CVPR_2023_paper.pdf) <br /> [![arXiv](https://img.shields.io/badge/arXiv-2211.11592-b31b1b.svg)](http://arxiv.org/abs/2211.11592) | [![YouTube](https://img.shields.io/badge/YouTube-%23FF0000.svg?style=for-the-badge&logo=YouTube&logoColor=white)](https://www.youtube.com/watch?v=7RgXJz_3kcg) |
 | K3DN: Disparity-Aware Kernel Estimation for Dual-Pixel Defocus Deblurring | :heavy_minus_sign: | [![thecvf](https://img.shields.io/badge/pdf-thecvf-7395C5.svg)](https://openaccess.thecvf.com//content/CVPR2023/papers/Yang_K3DN_Disparity-Aware_Kernel_Estimation_for_Dual-Pixel_Defocus_Deblurring_CVPR_2023_paper.pdf) | :heavy_minus_sign: |
 | Rawgment: Noise-Accounted RAW Augmentation Enables Recognition in a Wide Variety of Environments | :heavy_minus_sign: | [![thecvf](https://img.shields.io/badge/pdf-thecvf-7395C5.svg)](https://openaccess.thecvf.com//content/CVPR2023/papers/Yoshimura_Rawgment_Noise-Accounted_RAW_Augmentation_Enables_Recognition_in_a_Wide_Variety_CVPR_2023_paper.pdf) <br /> [![arXiv](https://img.shields.io/badge/arXiv-2210.16046-b31b1b.svg)](http://arxiv.org/abs/2210.16046) | :heavy_minus_sign: |