{"id":11407,"url":"https://github.com/murufeng/awesome-papers","name":"awesome-papers","description":"机器学习，深度学习，自然语言处理，计算机视觉方面的顶级期刊会议论文集","projects_count":45,"last_synced_at":"2026-08-27T20:00:35.653Z","repository":{"id":52059667,"uuid":"194481291","full_name":"murufeng/awesome-papers","owner":"murufeng","description":"机器学习，深度学习，自然语言处理，计算机视觉方面的顶级期刊会议论文集","archived":false,"fork":false,"pushed_at":"2020-07-08T02:43:06.000Z","size":65414,"stargazers_count":142,"open_issues_count":0,"forks_count":35,"subscribers_count":2,"default_branch":"master","last_synced_at":"2026-07-19T23:04:26.909Z","etag":null,"topics":["classification-algorithm","computer-vision","deep-learning","image-processing","machine-learning","natural-language-processing","object-detection"],"latest_commit_sha":null,"homepage":"https://github.com/murufeng/awesome-papers","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/murufeng.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2019-06-30T06:04:09.000Z","updated_at":"2026-07-05T00:54:17.000Z","dependencies_parsed_at":"2022-09-22T21:50:33.986Z","dependency_job_id":null,"html_url":"https://github.com/murufeng/awesome-papers","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/murufeng/awesome-papers","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/murufeng%2Fawesome-papers","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/murufeng%2Fawesome-papers/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/murufeng%2Fawesome-papers/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/murufeng%2Fawesome-papers/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/murufeng","download_url":"https://codeload.github.com/murufeng/awesome-papers/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/murufeng%2Fawesome-papers/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":36396262,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-08-06T04:43:03.162Z","status":"online","status_checked_at":"2026-08-08T02:00:08.763Z","response_time":96,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"created_at":"2024-01-12T20:23:31.425Z","updated_at":"2026-08-27T20:00:35.653Z","primary_language":null,"list_of_lists":false,"displayable":true,"categories":["目录","分享计算机视觉方向顶级期刊录用论文"],"sub_categories":["Object detection","deep_learning object detection","Embedding","Famous Machine Learning Papers","Google Three Papers","Image_Processing","NLP-progress","awesome-deep-learning-papers","Image-to-Image papers","Attention-Mechanisms-paper","GNN papers","Transfer Learning","Must-read Papers on Textual Adversarial Attack and Defense (TAAD)","Papers-of-Robust-ML"],"readme":"# 机器学习、深度学习、自然语言处理、计算机视觉论文集\n\n[![GitHub stars](https://img.shields.io/github/stars/murufeng/awesome-papers.svg?style=social\u0026label=Stars)](https://github.com/murufeng/awesome-papers) [![GitHub forks](https://img.shields.io/github/forks/murufeng/awesome-papers.svg?style=social\u0026label=Forks)](https://github.com/murufeng/awesome-papers) [![HitCount](http://hits.dwyl.io/murufeng/awesome-papers.svg)](http://hits.dwyl.io/murufeng/awesome-papers)\n\n## 目录\n\n### Object detection\n目标检测最全论文集锦\n* [Object detection](https://github.com/murufeng/papers/tree/master/Object-detection) \u003cbr /\u003e\n\n### deep_learning object detection\n* [A paper list of object detection using deep learning](https://github.com/murufeng/papers/blob/master/deep_learning%20object%20detection/papers.md) \u003cbr /\u003e\n\n\n### Embedding \n* [[Airbnb Embedding] Real-time Personalization using Embeddings for Search Ranking at Airbnb (Airbnb 2018)](https://github.com/murufeng/papers/blob/master/Embedding/%5BAirbnb%20Embedding%5D%20Real-time%20Personalization%20using%20Embeddings%20for%20Search%20Ranking%20at%20Airbnb%20(Airbnb%202018).pdf) \u003cbr /\u003e\n* [[Alibaba Embedding] Billion-scale Commodity Embedding for E-commerce Recommendation in Alibaba (Alibaba 2018)](https://github.com/murufeng/papers/blob/master/Embedding/%5BAlibaba%20Embedding%5D%20Billion-scale%20Commodity%20Embedding%20for%20E-commerce%20Recommendation%20in%20Alibaba%20(Alibaba%202018).pdf) \u003cbr /\u003e\n* [[Graph Embedding] DeepWalk- Online Learning of Social Representations (SBU 2014)](https://github.com/murufeng/papers/blob/master/Embedding/%5BGraph%20Embedding%5D%20DeepWalk-%20Online%20Learning%20of%20Social%20Representations%20(SBU%202014).pdf) \u003cbr /\u003e\n* [[Item2Vec] Item2Vec-Neural Item Embedding for Collaborative Filtering (Microsoft 2016)](https://github.com/murufeng/papers/blob/master/Embedding/%5BItem2Vec%5D%20Item2Vec-Neural%20Item%20Embedding%20for%20Collaborative%20Filtering%20(Microsoft%202016).pdf) \u003cbr /\u003e\n* [[Negative Sampling] Word2vec Explained Negative-Sampling Word-Embedding Method (2014)](https://github.com/murufeng/papers/blob/master/Embedding/%5BNegative%20Sampling%5D%20Word2vec%20Explained%20Negative-Sampling%20Word-Embedding%20Method%20(2014).pdf) \u003cbr /\u003e\n* [[Node2vec] Node2vec - Scalable Feature Learning for Networks (Stanford 2016)](https://github.com/murufeng/papers/blob/master/Embedding/%5BNode2vec%5D%20Node2vec%20-%20Scalable%20Feature%20Learning%20for%20Networks%20(Stanford%202016).pdf) \u003cbr /\u003e\n* [[SDNE] Structural Deep Network Embedding (THU 2016)](https://github.com/murufeng/papers/blob/master/Embedding/%5BSDNE%5D%20Structural%20Deep%20Network%20Embedding%20(THU%202016).pdf) \u003cbr /\u003e\n* [[Word2Vec] Distributed Representations of Words and Phrases and their Compositionality (Google 2013)](https://github.com/murufeng/papers/blob/master/Embedding/%5BWord2Vec%5D%20Distributed%20Representations%20of%20Words%20and%20Phrases%20and%20their%20Compositionality%20(Google%202013).pdf) \u003cbr /\u003e\n* [[Word2Vec] Word2vec Parameter Learning Explained (UMich 2016)](https://github.com/murufeng/papers/blob/master/Embedding/%5BWord2Vec%5D%20Word2vec%20Parameter%20Learning%20Explained%20(UMich%202016).pdf) \u003cbr /\u003e\n* [[Word2Vec] Efficient Estimation of Word Representations in Vector Space (Google 2013)](https://github.com/murufeng/papers/blob/master/Embedding/%5BWord2Vec%5D%20Efficient%20Estimation%20of%20Word%20Representations%20in%20Vector%20Space%20(Google%202013).pdf) \u003cbr /\u003e\n\n\n### Famous Machine Learning Papers\n* [[RNN] Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation (UofM 2014)](https://github.com/murufeng/papers/blob/master/Famous%20Machine%20Learning%20Papers/%5BRNN%5D%20Learning%20Phrase%20Representations%20using%20RNN%20Encoder%E2%80%93Decoder%20for%20Statistical%20Machine%20Translation%20(UofM%202014).pdf) \u003cbr /\u003e\n* [[CNN] ImageNet Classification with Deep Convolutional Neural Networks (UofT 2012)](https://github.com/murufeng/papers/blob/master/Famous%20Machine%20Learning%20Papers/%5BCNN%5D%20ImageNet%20Classification%20with%20Deep%20Convolutional%20Neural%20Networks%20(UofT%202012).pdf) \u003cbr /\u003e\n* [[Fast R-CNN]](https://github.com/murufeng/papers/blob/master/Famous%20Machine%20Learning%20Papers/Fast%20R-CNN.pdf) \u003cbr /\u003e\n\n### Google Three Papers\nGoogle三大篇，HDFS，MapReduce，BigTable，奠定大数据基础架构的三篇文章\n* [Bigtable A Distributed Storage System for Structured Data](https://github.com/murufeng/papers/blob/master/Google%20Three%20Papers/Bigtable%20A%20Distributed%20Storage%20System%20for%20Structured%20Data.pdf) \u003cbr /\u003e\n* [MapReduce Simplified Data Processing on Large Clusters](https://github.com/murufeng/papers/blob/master/Google%20Three%20Papers/MapReduce%20Simplified%20Data%20Processing%20on%20Large%20Clusters.pdf) \u003cbr /\u003e\n* [The Google File System](https://github.com/murufeng/papers/blob/master/Google%20Three%20Papers/The%20Google%20File%20System.pdf) \u003cbr /\u003e\n\n### Image_Processing\n* [CVPR19-FOCNet_ A Fractional Optimal Control Network for Image Denoising](https://github.com/murufeng/papers/blob/master/Image_Processing/CVPR19-FOCNet_%20A%20Fractional%20Optimal%20Control%20Network%20for%20Image%20Denoising_Lei%20Zhang.pdf) \u003cbr /\u003e\n* [Multi-Label Image Recognition with Graph Convolutional Networks](https://github.com/murufeng/papers/blob/master/Image_Processing/Multi-Label%20Image%20Recognition%20with%20Graph%20Convolutional%20Networks.pdf) \u003cbr /\u003e\n* [T-CNN](https://github.com/murufeng/papers/blob/master/Image_Processing/T-CNN.pdf) \u003cbr /\u003e\n\n### NLP-progress\n* [BERT_Pre-training of Deep Bidirectional Transformers for Language Understanding](https://github.com/murufeng/papers/blob/master/NLP-progress/BERT_Pre-training%20of%20Deep%20Bidirectional%20Transformers%20for%20Language%20Understanding.pdf) \u003cbr /\u003e\n* [Chinese Word Segmentation](https://github.com/murufeng/papers/blob/master/NLP-progress/Chinese%20Word%20Segmentation.md) \u003cbr /\u003e\n* [Dependency parsing](https://github.com/murufeng/papers/blob/master/NLP-progress/Dependency%20parsing.md) \u003cbr /\u003e\n* [Named entity recognition](https://github.com/murufeng/papers/blob/master/NLP-progress/Named%20entity%20recognition.md) \u003cbr /\u003e\n* [Text Classification](https://github.com/murufeng/papers/blob/master/NLP-progress/Text%20classification.md) \u003cbr /\u003e\n* [Word Sense Disambiguation](https://github.com/murufeng/papers/blob/master/NLP-progress/Word%20Sense%20Disambiguation.md) \u003cbr /\u003e\n* [XLNet_Generalized Autoregressive Pretraining for Language Understanding](https://github.com/murufeng/papers/blob/master/NLP-progress/XLNet_Generalized%20Autoregressive%20Pretraining%20for%20Language%20Understanding.pdf) \u003cbr /\u003e\n\n### awesome-deep-learning-papers\n深度学习（Deep Learning）的最全资料项目\n* [Most Cited Deep Learning Papers](https://github.com/murufeng/papers/blob/master/deep-learning-papers/Most%20Cited%20Deep%20Learning%20Papers.md) \u003cbr /\u003e\n\n\n### Image-to-Image papers\n* [Image to Image papers: A collection of image-to-image papers](https://github.com/murufeng/papers/blob/master/Image-to-Image%20papers.md)\n\n### Attention-Mechanisms-paper\n* [注意力机制在自然语言处理方面的文章笔记](https://github.com/murufeng/papers/blob/master/Attention-Mechanisms-paper.md) \u003cbr /\u003e\n\n\n### GNN papers\n* [[Must-read papers on GNN] GNN: graph neural network](https://github.com/murufeng/papers/blob/master/GNN_papers.md) \u003cbr /\u003e\n* [Hands on Graph Neural Networks with PyTorch \u0026 PyTorch Geometric](https://github.com/murufeng/papers/blob/master/Hands%20on%20Graph%20Neural%20Networks%20with%20PyTorch%20%26%20PyTorch%20Geometric.pdf) \u003cbr /\u003e\n\n\n### Transfer Learning\n迁移学习相关文章,主要介绍迁移学习在自然语言处理中的运用\n* [Transfer Learning in Natural Language Processing](https://github.com/murufeng/papers/blob/master/Transfer%20Learning%20in%20Natural%20Language%20Processing.pdf) \u003cbr /\u003e\n* [Transfer Learning with Convolutional Neural Networks in PyTorch](https://github.com/murufeng/papers/blob/master/Transfer%20Learning%20with%20Convolutional%20Neural%20Networks%20in%20PyTorch.pdf) \u003cbr /\u003e\n\n\n### Must-read Papers on Textual Adversarial Attack and Defense (TAAD)\n* [Must-read Papers on Textual Adversarial Attack and Defense (TAAD)](https://github.com/murufeng/papers/blob/master/TAADpapers.md) \u003cbr /\u003e\n\n### Papers-of-Robust-ML\n* [Related papers for robust machine learning](https://github.com/murufeng/papers/blob/master/Papers-of-Robust-ML.md)\n\n\n## 分享计算机视觉方向顶级期刊录用论文\n\n**CVPR**\n- 2020 \n  - [CVPR2020录用论文清单](http://cvpr2020.thecvf.com/)\n  - [CVPR2020论文列表和代码汇总](https://github.com/murufeng/awesome-papers/tree/master/CVPR%202020)\n\n- 2019\n  - [CVPR 2019所有录用论文清单](\u003chttp://openaccess.thecvf.com/CVPR2019.py\u003e) \n  - CVPR 2019论文PDF下载（1294篇论文）：[百度云链接](https://pan.baidu.com/s/1WMOU3JgeKsYA0YCeW09uHw ) 密码: b7uj\n- 2018\n  - [CVPR 2018所有录用论文清单](2018/cvpr2018-paper-list.csv) \n  - CVPR 2018论文PDF下载（979篇论文）：[百度云链接](https://pan.baidu.com/s/1lYEM_kkw1PWTkQzUvjG2pw)   密码: 6pgk \n- 2017\n  - CVPR 2017论文PDF下载：[百度云链接](https://pan.baidu.com/s/1RP1wQBFxs8BT0KBLiukxBw)   密码: hnzg\n\n**ECCV**\n- 2020 \n  - [ECCV2020接受论文列表](https://eccv2020.eu/accepted-papers/)\n\n- 2018\n  - [ECCV 2018所有录用论文清单](http://openaccess.thecvf.com/ECCV2018.py) \n  - ECCV 2018论文PDF下载：[百度云链接](https://pan.baidu.com/s/1Mg0Kw9bepUK6_vqqVSOjNQ)   密码: mh97\n  \n**ICCV 2019**\n\n- 2019\n  - ICCV 2019论文下载：[百度云链接](https://pan.baidu.com/s/1yeA8qNkkb92Z0vA-8h2FTg)  密码：nynu\n","projects_url":"https://awesome.ecosyste.ms/api/v1/lists/murufeng%2Fawesome-papers/projects"}