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本文会议包括、CVPR、ECCV、IJCAI、AAAI、ICML、NIPS
ICCV：International Conference on Computer Vision
CVPR：International Conference on Computer Vision and Pattern Recognition
ECCV：European Conference on Computer Vision
IJCAI：International Joint Conference on Artificial Intelligence
AAAI：National Conference on Artificial Intelligence
ICML：International Conference on Machine Learning
NIPS：Conference and Workshop on Neural Information Processing Systems
ICLR：International Conference on Learning Representations
ICCV的全称是International Conference on Computer Vision，ICCV两年一次。近几届具体举办日期、举办城市及截稿时间如下：
| Event | When | Where | Deadline |
| ICCV 2019 | International Conference on Computer Vision | ||
| Oct 27, 2019 - Nov 3, 2019 | Seoul, Korea | Mar 1, 2019 | |
| ICCV 2017 | International Conference on Computer Vision | ||
| Oct 22, 2017 - Oct 29, 2017 | Venice, Italy | Mar 17, 2017 | |
| ICCV 2013 | IEEE International Conference on Computer Vision | ||
| Dec 1, 2013 - Dec 8, 2013 | Sydney, Australia | Apr 12, 2013 (Apr 8, 2013) | |
| ICCV 2011 | The 13th International Conference on Computer Vision | ||
| Nov 6, 2011 - Nov 13, 2011 | Barcelona, Spain | Mar 1, 2011 | |
| ICCV 2009 | International Conference on Computer Vision | ||
| Sep 29, 2009 - Oct 2, 2009 | Kyoto, Japan | Mar 10, 2009 | |
ICCV2019投稿要求：
Papers in the main technical program must describe high-quality, original research. Topics of interest include all aspects of computer vision and pattern recognition including, but not limited to
3D Computer Vision
Action Recognition
Big data and Large Scale Methods
Biometrics, face and gesture
Biomedical image analysis
Computational photography, photometry, shape from X
Deep Learning
Low-level vision and Image Processing
Motion and Tracking
Optimization methods
Recognition: detection, categorization, indexing and matching
Robot Vision
Segmentation, grouping and shape representation
Statistical learning
Video: events, activities and surveillance
Vision for X
ICCV2019论文下载地址：
http://openaccess.thecvf/ICCV2019.py（修改相应年份即可定向搜索每届会议论文）
CVPR的全称是International Conference on Computer Vision and Pattern Recognition，这是一个一年一次的会议。近几届具体举办日期、举办城市及截稿时间如下：
| Event | When | Where | Deadline |
| CVPR 2020 | Computer Vision and Pattern Recognition | ||
| Jun 16, 2020 - Jun 20, 2020 | Seattle, WA | Nov 15, 2019 | |
| CVPR 2019 | Computer Vision and Pattern Recognition | ||
| Jun 15, 2019 - Jun 21, 2019 | Long Beach, CA | Nov 16, 2018 | |
| CVPR 2018 | Computer Vision and Pattern Recognition | ||
| Jun 18, 2018 - Jun 22, 2018 | SALT LAKE CITY, UTAH | Nov 15, 2017 (Nov 8, 2017) | |
CVPR2020投稿要求：
Call for Papers
Papers in the main technical program must describe high-quality, original research. Topics of interest include all aspects of computer vision and pattern recognition including, but not limited to
3D computer vision
Action and behavior recognition
Adversarial learning, adversarial attack and defense methods
Biometrics, face, gesture, body pose
Computational photography, image and video synthesis
Datasets and evaluation
Efficient training and inference methods for networks
Explainable AI, fairness, accountability, privacy, transparency and ethics in vision
Image retrieval
Low-level and physics-based vision
Machine learning architectures and formulations
Medical, biological and cell microscopy
Motion and tracking
Neural generative models, auto encoders, GANs
Optimization and learning methods
Recognition (object detection, categorization)
Representation learning, deep learning
Scene analysis and understanding
Segmentation, grouping and shape
Transfer, low-shot, semi- and un- supervised learning
Video analysis and understanding
Vision + language, vision + other modalities
Vision applications and systems, vision for robotics and autonomous vehicles
Visual reasoning and logical representation
All submissions will be handled electronically. In addition to the main technical program, the conference will include Tutorials, Workshops, Demonstrations, and Exhibits. Submit proposals to the appropriate chair.
CVPR2019论文下载地址：
http://openaccess.thecvf/CVPR2019.py（修改相应年份即可定向搜索每届会议论文）
ECCV的全称是European Conference on Computer Vision，是一个欧洲的会议，两年举办一次，与ICCV刚好错开。近几届具体举办日期、举办城市及截稿时间如下：
| Event | When | Where | Deadline |
| ECCV 2020 | European Conference on Computer Vision | ||
| Aug 23, 2020 - Aug 28, 2020 | Glasgow | TBD | |
| ECCV 2018 | European Conference on Computer Vision | ||
| Sep 8, 2018 - Sep 14, 2018 | Munich, Germany | Mar 14, 2018 | |
| ECCV 2012 | European Conference on Computer Vision | ||
| Oct 7, 2012 - Oct 13, 2012 | Florence, Italy | Mar 5, 2012 | |
| ECCV 2010 | 11th European Conference on Computer Vision | ||
| Sep 5, 2010 - Sep 11, 2010 | Hersonissos, Crete, Greece | Mar 17, 2010 | |
| ECCV 2008 | 10th European Conference on Computer Vision | ||
| Oct 12, 2008 - Oct 18, 2008 | Marseille, France | Mar 17, 2008 | |
ECCV2010投稿要求（2010投稿要求较为详细）：
ECCV is a selective single-track conference on computer vision. High quality previously unpublished research contributions are sought on any aspect of computer vision.
Topics include, but are not limited to:
* Sensors and Early Vision
* Image Features
* Color and Texture
* Segmentation and Grouping
* Image-Based Modeling
* Illumination and Reflectance Modeling
* Motion and Tracking
* Stereo and Structure from Motion
* Shape Representation
* Object Recognition
* Video Analysis
* Event Detection and Recognition
* Face Detection and Recognition
* Gesture Recognition
* Statistical Models and Visual Learning
* Medical Image Analysis
* Active and Robot Vision
* Image and Video Retrieval
* Cognitive & Biologically inspired Vision
* Vision Systems Engineering & Performance Evaluation
ECCV2019论文下载地址：http://openaccess.thecvf/ECCV2018.py
IJCAI : International Joint Conference on Artificial Intelligence，国际人工智能联合会议，一年一次。近几届具体举办日期、举办城市及截稿时间如下：
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IJCAI投稿要求严格，具体参考http://www.wikicfp/cfp/program?id=1567&s=IJCAI&f=International%20Joint%20Conference%20on%20Artificial%20Intelligence。
IJCAI2019论文下载地址：https://www.ijcai/proceedings/2019/。
AAAI:National Conference on Artificial Intelligence，人工智能会议，一年一次。近几届具体举办日期、举办城市及截稿时间如下：
| Event | When | Where | Deadline |
| AAAI 2020 | The Thirty-Fourth AAAI Conference on Artificial Intelligence | ||
| Feb 7, 2020 - Feb 12, 2020 | Hilton New York Midtown, New York, USA | Sep 5, 2019 (Aug 30, 2019) | |
| AAAI 2019 | National Conference on Artificial Intelligence | ||
| Jan 27, 2019 - Feb 1, 2019 | Honolulu, Hawaii | Sep 5, 2018 (Sep 1, 2018) | |
| AAAI 2018 | The Thirty-Second AAAI Conference on Artificial Intelligence | ||
| Feb 2, 2018 - Feb 7, 2018 | New Orleans, Lousiana, USA | Sep 11, 2017 (Sep 8, 2017) | |
| AAAI 2016 | Thirtieth AAAI Conference on Artificial Intelligence | ||
| Feb 12, 2016 - Feb 17, 2016 | Phoenix, Arizona, USA | Sep 15, 2015 (Sep 10, 2015) | |
AAAI2020大会主题以及投稿范围：
The purpose of the AAAI conference series is to promote research in artificial intelligence (AI) and foster scientific exchange between researchers, practitioners, scientists, students, and engineers in AI and its affiliated disciplines. AAAI-20 is the Thirty-Fourth AAAI Conference on Artificial Intelligence. It will continue the tradition of previous AAAI conferences with technical paper presentations, invited speakers, workshops, tutorials, poster sessions, senior member presentations, competitions, and exhibit programs, all selected according to the highest standards. AAAI-20 will also include additional programs for students and young researchers.
Topics
AAAI-20 welcomes submissions reporting research that advances artificial intelligence, broadly conceived. The conference scope includes all subareas of AI and machine learning. These include (but are not limited to) traditional topics such as search, planning, knowledge representation, reasoning, natural language processing, robotics and perception, multiagent systems, statistical learning, and deep learning. We expressly encourage work that cuts across technical areas, or develops AI techniques in the context of important application domains, such as healthcare, sustainability, transportation, and commerce.
AAAI2019论文下载地址：https://dblp.uni-trier.de/db/conf/aaai/aaai2019.html
ICML:International Conference on Machine Learning，机器学习的国际会议，一年一次。近几届具体举办日期、举办城市及截稿时间如下：
| Event | When | Where | Deadline |
| ICML 2020 | 37th International Conference on Machine Learning | ||
| Jul 12, 2020 - Jul 18, 2020 | Vienna, AUSTRIA | Feb 7, 2020 (Jan 31, 2020) | |
| ICML 2019 | 36th International Conference on Machine Learning | ||
| Jun 10, 2019 - Jun 15, 2019 | Long Beach, CA, USA | Jan 23, 2019 (Jan 18, 2019) | |
| ICML 2018 | The 35th International Conference on Machine Learning | ||
| Jul 10, 2018 - Jul 15, 2018 | Stockholmsmässan, Stockholm SWEDEN | Feb 9, 2018 | |
| ICML 2017 | 34th International Conference on Machine Learning | ||
| Aug 6, 2017 - Aug 11, 2017 | Sydney, Australia | Feb 24, 2017 | |
ICML大会主题以及投稿范围：接收所有范围的机器学习论文，详细参考http://www.wikicfp/cfp/servlet/event.showcfp?eventid=81548©ownerid=122241
ICML以及各种机器学习论文下载地址：
http://proceedings.mlr.press/
NIPS：神经信息处理系统大会(Conference and Workshop on Neural Information Processing Systems)。一般是每年的12月举行，机器学习领域的顶级会议。近几届具体举办日期、举办城市及截稿时间如下：
| Event | When | Where | Deadline |
| NIPS 2019 | Thirty-third Conference on Neural Information Processing Systems | ||
| Dec 10, 2019 - Dec 12, 2019 | Vancouver, Canada | May 23, 2019 (May 16, 2019) | |
| NIPS 2018 | The Thirty-second Annual Conference on Neural Information Processing Systems | ||
| Dec 3, 2018 - Dec 8, 2018 | Montréal, CANADA | TBD | |
| NIPS 2017 | The Thirty-first Annual Conference on Neural Information Processing Systems | ||
| Dec 4, 2017 - Dec 9, 2017 | Long Beach, CA, USA | May 19, 2017 | |
NIPS2018投稿接收范围：
Submissions are solicited for the Thirty-Second Annual Conference on Neural Information Processing Systems (NIPS 2018), a multi track, interdisciplinary conference that brings together researchers in machine learning, computational neuroscience, and their applications.
Subject areas include:
Algorithms: Active Learning; Adaptive Data Analysis; AutoML; Bandit Algorithms; Boosting and Ensemble Methods; Classification; Clustering; Collaborative Filtering; Components Analysis (e.g., CCA, ICA, LDA, PCA); Density Estimation; Dynamical Systems; Kernel Methods; Large Margin Methods; Metric Learning; Missing Data; Model Selection and Structure Learning; Multitask and Transfer Learning; Nonlinear Dimensionality Reduction and Manifold Learning; Online Learning; Ranking and Preference Learning; Regression; Relational Learning; Representation Learning; Semi-Supervised Learning; Similarity and Distance Learning; Sparse Coding and Dimensionality Expansion; Sparsity and Compressed Sensing; Spectral Methods; Stochastic Methods; Structured Prediction; Unsupervised Learning.
Applications: Activity and Event Recognition; Audio and Speech Processing; Body Pose, Face, and Gesture Analysis; Communication- or Memory-Bounded Learning; Computational Biology and Bioinformatics; Computational Photography; Computational Social Science; Computer Vision; Denoising; Dialog- or Communication-Based Learning; Fairness, Accountability, and Transparency; Game Playing; Hardware and Systems; Image Segmentation; Information Retrieval; Matrix and Tensor Factorization; Motor Control; Music Modeling and Analysis; Natural Language Processing; Natural Scene Statistics; Network Analysis; Object Detection; Object Recognition; Privacy, Anonymity, and Security; Quantitative Finance and Econometrics; Recommender Systems; Robotics; Signal Processing; Source Separation; Speech Recognition; Sustainability; Systems Biology; Text Analysis; Time Series Analysis; Tracking and Motion in Video; Video Analysis; Video Segmentation; Visual Features; Visual Question Answering; Visual Scene Analysis and Interpretation; Web Applications and Internet Data.
Data, Competitions, Implementations, and Software: Benchmarks; Competitions or Challenges; Data Sets or Data Repositories; Software Toolkits.
Deep Learning: Adversarial Networks; Attention Models; Biologically Plausible Deep Networks; CNN Architectures; Deep Autoencoders; Efficient Inference Methods; Efficient Training Methods; Embedding Approaches; Few-Shot Learning Approaches; Generative Models; Interaction-Based Deep Networks; Memory-Augmented Neural Networks; Meta-Learning; Neural Abstract Machines; Optimization for Deep Networks; Predictive Models; Program Induction; Recurrent Networks; Supervised Deep Networks; Virtual Environments; Visualization or Exposition Techniques for Deep Networks.
Neuroscience and Cognitive Science: Auditory Perception; Brain Imaging; Brain Mapping; Brain Segmentation; Brain--Computer Interfaces and Neural Prostheses; Cognitive Science; Connectomics; Human or Animal Learning; Language for Cognitive Science; Memory; Neural Coding; Neuropsychology; Neuroscience; Perception; Plasticity and Adaptation; Problem Solving; Reasoning; Spike Train Generation; Synaptic Modulation; Visual Perception.
Optimization: Combinatorial Optimization; Convex Optimization; Non-Convex Optimization; Submodular Optimization.
Probabilistic Methods: Bayesian Nonparametrics; Bayesian Theory; Belief Propagation; Causal Inference; Distributed Inference; Gaussian Processes; Graphical Models; Hierarchical Models; Latent Variable Models; MCMC; Topic Models; Variational Inference.
Reinforcement Learning and Planning: Decision and Control; Exploration; Hierarchical RL; Markov Decision Processes; Model-Based RL; Multi-Agent RL; Navigation; Planning; Reinforcement Learning.
Theory: Competitive Analysis; Computational Complexity; Control Theory; Frequentist Statistics; Game Theory and Computational Economics; Hardness of Learning and Approximations; Information Theory; Large Deviations and Asymptotic Analysis; Learning Theory; Regularization; Spaces of Functions and Kernels; Statistical Physics of Learning.
NIPS历年论文下载地址：https://papers.nips/
ICLR：International Conference on Learning Representations（国际学习表征会议），深度学习方面的顶级会议。近几届具体举办日期、举办城市及截稿时间如下：
| Event | When | Where | Deadline |
| ICLR 2016 | ICLR 2016 : International Conference on Learning Representations 2016 | ||
| May 2, 2016 - May 4, 2016 | San Juan, Puerto Rico | Nov 19, 2015 (Nov 12, 2015) | |
| ICLR 2017 | 5th International Conference on Learning Representations | ||
| Apr 24, 2017 - Apr 26, 2017 | Palais des Congrès Neptune, Toulon, Fr | Nov 4, 2016 | |
| ICLR 2019 | International Conference for Learning Representations | ||
| Apr 30, 2019 - Apr 30, 2019 | New Orleans | Sep 27, 2018 | |
| ICLR 2020 | International Conference on Learning Representations | ||
| Apr 26, 2020 - Apr 30, 2020 | Millennium Hall, Addis Ababa ETHIOPIA | Sep 25, 2019 | |
ICLR2018投稿接收范围：
Overview
The performance of machine learning methods is heavily dependent on the choice of data representation (or features) on which they are applied. The rapidly developing field of deep learning is concerned with questions surrounding how we can best learn meaningful and useful representations of data. We take a broad view of the field and include topics such as feature learning, metric learning, compositional modeling, structured prediction, reinforcement learning, and issues regarding large-scale learning and non-convex optimization. The range of domains to which these techniques apply is also very broad, from vision to speech recognition, text understanding, gaming, music, etc.
A non-exhaustive list of relevant topics:
unsupervised, semi-supervised, and supervised representation learning
representation learning for planning and reinforcement learning
metric learning and kernel learning
sparse coding and dimensionality expansion
hierarchical models
optimization for representation learning
learning representations of outputs or states
implementation issues, parallelization, software platforms, hardware
applications in vision, audio, speech, natural language processing, robotics, neuroscience, or any other field
The program will include keynote presentations from invited speakers, oral presentations, and posters.
ICLR features two tracks: a Conference Track and a Workshop Track. Submissions of extended abstracts to the Workshop Track will be accepted after the decision notifications for Conference Track submissions are sent. A future call for extended abstracts will provide more details on the Workshop Track.
Some of the submitted Conference Track papers that are not accepted to the conference proceedings will be invited for presentation in the Workshop Track.
ICLR论文下载地址：https://chillee.github.io/OpenReviewExplorer/index.html
该地址将ICLR会议论文进行了评分并排名。
最后，
前往https://openreview/可查看许多会议提交的论文。
前往http://openaccess.thecvf/menu.py查看计算机视觉顶会论文。
前往https://dblp2.uni-trier.de/搜索会议论文。
前往http://www.wikicfp/cfp/series?t=c&i=A查看各种会议的召开时间、举办地点、投稿日期、投稿要求、审核流程等信息。
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