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Ultimate Context Engineering Infrastructure, starting from MCPs and Integrations
A complete computer science study plan to become a software engineer.
ChatGLM2-6B: An Open Bilingual Chat LLM | 开源双语对话语言模型
《代码随想录》LeetCode 刷题攻略：200道经典题目刷题顺序，共60w字的详细图解，视频难点剖析，50余张思维导图，支持C++，Java，Python，Go，JavaScript等多语言版本，从此算法学习不再迷茫！🔥🔥 来看看，你会发现相见恨晚！🚀
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), ga…
Designing a Practical Degradation Model for Deep Blind Image Super-Resolution (ICCV, 2021) (PyTorch) - We released the training code!
2018/2019/校招/春招/秋招/自然语言处理(NLP)/深度学习(Deep Learning)/机器学习(Machine Learning)/C/C++/Python/面试笔记，此外，还包括创建者看到的所有机器学习/深度学习面经中的问题。 除了其中 DL/ML 相关的，其他与算法岗相关的计算机知识也会记录。 但是不会包括如前端/测试/JAVA/Android等岗位中有关的问题。
CV算法岗知识点及面试问答汇总，主要分为计算机视觉、机器学习、图像处理和 C++基础四大块，一起努力向offers发起冲击！
TDAN: Temporally-Deformable Alignment Network for Video Super-Resolution, CVPR 2020
A runable Pytorch implementation of Local Relation Layer for the paper Local Relation Networks for Image Recognition
GeoNet: Geometric Neural Network for Joint Depth and Surface Normal Estimation
Implementation of the paper, "LIME: Low-Light Image Enhancement via Illumination Map Estimation"
Implementation of CVPR 2020 Dual Super-Resolution Learning for Semantic Segmentation
Underexposed Photo Enhancement Using Deep Illumination Estimation
Dual Super-Resolution Learning for Semantic Segmentation
adding denoise to the previous work
Self-supervised Image Enhancement Network: Training With Low Light Images Only
Tensorflow implementation of the SRGAN algorithm for single image super-resolution
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
Tensorflow implementation of Enhanced Deep Residual Networks for Single Image Super-Resolution
Second-order Attention Network for Single Image Super-resolution (CVPR-2019)
My resume in LaTeX (template suited for new graduates; 应届生简历模板)
A Pytorch-Lightning implementation of self-supervised algorithms