enter-i-username

enter-i-username's Stars

• PlexPt/awesome-chatgpt-prompts-zh

  ChatGPT 中文调教指南。各种场景使用指南。学习怎么让它听你的话。

  53.6k3479613.6k

• lencx/ChatGPT

  🔮 ChatGPT Desktop Application (Mac, Windows and Linux)

  Language:Rust53.4k4461.1k6k

• microsoft/Bringing-Old-Photos-Back-to-Life

  Bringing Old Photo Back to Life (CVPR 2020 oral)

  Language:Python15.3k2882552k

• dragen1860/Deep-Learning-with-TensorFlow-book

  深度学习入门开源书，基于TensorFlow 2.0案例实战。Open source Deep Learning book, based on TensorFlow 2.0 framework.

  Language:Jupyter Notebook13.2k4872204.1k

• milesial/Pytorch-UNet

  PyTorch implementation of the U-Net for image semantic segmentation with high quality images

  Language:Python9.5k714492.5k

• facebookresearch/mae

  PyTorch implementation of MAE https//arxiv.org/abs/2111.06377

  Language:Python7.5k571941.2k

• gkamradt/langchain-tutorials

  Overview and tutorial of the LangChain Library

  Language:Jupyter Notebook6.8k110362k

• mseitzer/pytorch-fid

  Compute FID scores with PyTorch.

  Language:Python3.5k1386518

• hyunwoongko/transformer

  Transformer: PyTorch Implementation of "Attention Is All You Need"

  Language:Python3.2k1022456

• XPixelGroup/HAT

  CVPR2023 - Activating More Pixels in Image Super-Resolution Transformer Arxiv - HAT: Hybrid Attention Transformer for Image Restoration

  Language:Python1.3k19155158

• Syan-Lin/CyberWaifu

  LLM + TTS 的真实感聊天机器人 | QQ 机器人 | 支持表情包、QQ 表情、联网搜索

  Language:Python1k950120

• ZhendongWang6/Uformer

  [CVPR 2022] Official implementation of the paper "Uformer: A General U-Shaped Transformer for Image Restoration".

  Language:Python8231181119

• cjyaddone/ChatWaifu

  Combined ChatGPT with Moegoe TTS to create a Chatting Waifu

  Language:Python822112189

• Tencent/Real-SR

  Real-World Super-Resolution via Kernel Estimation and Noise Injection

  Language:Python7931833118

• TeaPearce/Conditional_Diffusion_MNIST

  Conditional diffusion model to generate MNIST. Minimal script. Based on 'Classifier-Free Diffusion Guidance'.

  Language:Python6964977

• DarrenPan/Awesome-CVPR2024-Low-Level-Vision

  A Collection of Papers and Codes in CVPR2023/2022 about low level vision

  65623250

• swz30/CycleISP

  [CVPR 2020--Oral] CycleISP: Real Image Restoration via Improved Data Synthesis

  Language:Python516152774

• huawei-noah/Pretrained-IPT

  Language:Python453105963

• jinyeying/night-enhancement

  [ECCV2022] "Unsupervised Night Image Enhancement: When Layer Decomposition Meets Light-Effects Suppression", https://arxiv.org/abs/2207.10564

  Language:HTML41452736

• aasharma90/RetinexNet_PyTorch

  Unofficial PyTorch code for the paper - Deep Retinex Decomposition for Low-Light Enhancement, BMVC'18

  Language:Python2042928

• DarrenPan/Awesome-ICCV2023-Low-Level-Vision

  A Collection of Papers and Codes in ICCV2023/2021 about low level vision

  1948014

• sanghyun-son/bicubic_pytorch

  A PyTorch implementation of widely-used bicubic interpolation, which is fully compatible with MATLAB.

  Language:Python1371223

• miaoyuchun/DDS2M

  The official implementation of DDS2M [ICCV 2023].

  Language:Python111224

• BaiShuanghao/Prompt-based-Distribution-Alignment

  [AAAI 2024] Prompt-based Distribution Alignment for Unsupervised Domain Adaptation

  Language:Python521113

• JiangHe96/DL4sSR

  Benchmark for a paper submitted to Information Fusion

  Language:Python35103

• LinaZhuang/FastHyDe_FastHyIn

  The code and data herein distributed reproduce the results published in the paper: Lina Zhuang and Jose M. Bioucas-Dias, "Hyperspectral image denoising and inpainting based on low-rank and sparse representations", Submitted to IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2017.

  Language:MATLAB19202

• Yb1t/ExDark2Yolo

  Convert ExDark annotated format data to YOLO format data. / 将ExDark标注格式的数据转换成YOLO格式的数据

  Language:Python19122

• DarrenPan/Awesome-NeurIPS2023-Low-Level-Vision

  A Collection of Papers and Codes in NeurIPS2022/2021 related to Low-Level Vision

  18200

• Magic-lem/MeSAM

  This is the official PyTorch implementation of the paper

  Language:Python14440

• polwork/No-Reference-Hyperspectral-Image-Quality-Assessment-via-Quality-Sensitive-Features-Learning

  code for paper "Yang, J., Zhao, Y., Yi, C., & Chan, J. C. W. (2017). No-Reference Hyperspectral Image Quality Assessment via Quality-Sensitive Features Learning. Remote Sensing, 9(4), 305."

  Language:MATLAB7125