Zhiyuan community AI weekly 78: CVPR 2021 publishes best paper
2021-06-23 23:58:22 【Author: Lou】
In order to help Chinese AI research 、 Practitioners can better understand the latest information in the field of global artificial intelligence , This week, the editorial team of Zhiyuan Research Institute compiled the second 78 period 《 Zhiyuan community AI weekly 》, From the academic （ Papers and new ideas 、 Academic conferences, etc ）, Industry and policy （ Technology industry policy 、 Project fund application 、 Technology investment and financing, etc ）, figure （ Personnel changes and awards of scholars ）、 data （ Data sets ）, Tools （ New tools and applications recommended ） And so on , A bird's-eye view of what's happening in AI in the past week .
In the past week （2021/06/14~2021/06/20）, The following are noteworthy contents 3 aspect ：
One 、 In recent days, ,CVPR 2021 Published the best paper 、 Best student thesis, etc . Researchers from Marple Institute and tibingen University in Germany won the best paper award , Researchers at Caltech and Northwestern University won the best student thesis Award . Besides ,FAIR Two Chinese scholars, including he Kaiming, were nominated for the best paper , And another Chinese scholar 、 Lin Shanchuan, a graduate student in the Department of computer science at the University of Washington, was nominated for the best student thesis .（ See this week for details “ meeting ” The column ）
Two 、 In recent days, ,ACM SIG The results of the new election , Chen Yiran 、 Liu Xue 、 Wang Wei 、 Wang xiaofeng 、May Dongmei Wang、Lili Qiu And so on , The term of office is 2021 year 7 month 1 solstice 2023 year 6 month 30 Japan .（ See this week for details “ figure ” The column ）
3、 ... and 、 The study was conducted by DeepMind Chief research scientist 、 Professor at University College London David Silver Leading , The research inspiration comes from their research on the evolution of natural intelligence and the latest achievements of artificial intelligence , At the time of writing the paper, it is still in the pre proof stage . The researchers believe that , Reward maximization and trial and error experience are enough to develop the ability to show behavior related to intelligence . thus , They came to the conclusion that , Reinforcement learning is a branch of artificial intelligence based on reward maximization , It can promote the development of general artificial intelligence .（ See this week for details “ Point of view ” The column ）
Here are the details of each point .
tsinghua 、 National People's Congress 、 Fudan, etc | Pre training model ： In the past 、 Present and future
Transformer | THUNDR： Tag based Transformer Of 3D Human body reconstruction
Robust learning | Against visual robustness based on causal intervention
GNN | Rotation invariant graph neural networks using spin convolution
Medical image segmentation | Unsupervised domain adaptive optimal latent vector alignment in medical image segmentation
Point of view
DeepMind Chief research scientist 、 Professor at University College London David Silver： Reinforcement learning can promote general AI
The study was conducted by DeepMind Chief research scientist 、 Professor at University College London David Silver Leading , The research inspiration comes from their research on the evolution of natural intelligence and the latest achievements of artificial intelligence , At the time of writing the paper, it is still in the pre proof stage . The researchers believe that , Reward maximization and trial and error experience are enough to develop the ability to show behavior related to intelligence . thus , They came to the conclusion that , Reinforcement learning is a branch of artificial intelligence based on reward maximization , It can promote the development of general artificial intelligence .
Industry and Policy
Google's autopilot Division Waymo Recapture 25 Us $100 million financing
According to Reuters 6 month 16 It's reported that , Google's autopilot Division ——Waymo Get... In a new round of financing 25 Billion dollars investment . It is reported that , Google parent Alphabet Participated in this round of financing , Other investors include Andreessen Horowitz、Silver Lake and Tiger Global etc. . According to the investor website PitchBook The data of ,Waymo The latest valuation of is over 300 Billion dollars .Waymo Founded on 2009 year , It has become a leader in the field of completely driverless .Waymo Is the world's first commercial taxi Hailing service for passengers Waymo One, Already in Phoenix 、 San Francisco and the bay area are in operation .Waymo Express , This round of financing includes 10 Multiple investors , The financing will be used to advance the company's autonomous driving technology Waymo Driver, And used to expand Waymo The team .
ACM SIG The list of new presidents is announced ！ Chen Yiran 、 Liu Xue and six other Chinese scholars were elected
Texas A & M University 、 University of Texas at Austin | Self destructive comparative learning
The university of Hong Kong | HR-NAS： Use lightweight Transformer Search for efficient high resolution neural architecture
High resolution representation (HR) For intensive forecasting tasks （ For example, segmentation 、 Detection and attitude estimation ） crucial . In the past, neural architecture search focused on image classification (NAS) In the method , Study HR The expression is usually ignored . This work presents a new NAS Method , be called HR-NAS, It can effectively encode multi-scale context information while maintaining high-resolution representation , Find effective and accurate networks for different tasks . stay HR-NAS in , We updated it NAS Search space and search strategy . In order to be in HR-NAS Better coding of multi-scale image context in search space , We first designed a lightweight Converter , Its computational complexity can be changed dynamically according to different objective functions and computational budgets . In order to maintain the high-resolution representation of the learning network ,HR-NAS Adopt multi branch architecture , suffer HRNet Inspired by the , Convolutional coding that provides multiple feature resolutions . Last , We propose an effective fine-grained search strategy to train HR-NAS, It effectively explores the search space , And find the best architecture given a variety of tasks and computing resources . HR-NAS It can be used in three intensive prediction tasks and one image classification task FLOP To achieve the most advanced trade-off between , As long as the budget is small . for example ,HR-NAS Beyond the design for semantic segmentation SqueezeNAS, At the same time, it improves 45.9% The efficiency of .
Well quickly |MlTr： Using converters for multi label classification
Netease is open source EMLL： High performance end side machine learning computing library
With the development of artificial intelligence technology , We have higher and higher requirements for computing performance . Most of the traditional computing processing is based on the cloud side , Put all the images 、 Audio and other data are transmitted to the cloud center through the network for processing, and then the results are fed back . But as the data grows exponentially , Relying on cloud computing has shown many shortcomings , For example, real-time data processing 、 Network constraints 、 Data security, etc , So end-to-end reasoning becomes more and more important . In this context , NetEase has a way AI The team independently designed and developed a high-performance end side machine learning computing library ——EMLL(Edge ML Library), And it has been open source recently .
Chinese University of Hong Kong | DistillFlow： A self supervised learning framework for optical flow estimation
We proposed DistillFlow, This is a knowledge distillation method for learning optical flow .DistillFlow Training multiple teacher models and student models , Among them, the challenging transformation is applied to the input of student model to generate illusion occlusion and less confident prediction . then , A self supervised learning framework is constructed ： Confidence predictions from teacher models are used as annotations , To guide the student model for those less confident prediction learning optical flow . Self supervised learning framework enables us to learn optical flow effectively from unlabeled data , Not only for non occluded pixels , It also applies to occluded pixels . DistillFlow stay KITTI and Sintel State of the art unsupervised learning performance on datasets . Our self supervised pre training model also provides excellent initialization for supervised fine tuning , This shows that compared with the current supervised learning method which highly relies on synthetic data pre training , It's an alternative training paradigm . At the time of writing , Our fine tuning model is KITTI 2015 Ranked first of all the monocular methods for benchmarking , And in Sintel Final Performance in benchmarking is better than all published methods . what's more , We've shown... In three ways DistillFlow Generalization ability ： Frame generalization 、 Corresponding generalization and cross dataset generalization .
University of Chinese Academy of Sciences | Uformer： General purpose for image restoration U shape Transformer
In this paper , We proposed Uformer, This is an effective and efficient method based on Transformer The architecture of , We use Transformer Block building layered encoders - Decoder network for image restoration . Uformer There are two core designs , Make it fit for the task . The first key element is the locally enhanced window Transformer block , We use non overlapping window based self attention to reduce computational requirements , The depth convolution is used in the feedforward network to further improve its capture potential . The second key element is that we've explored three ways to skip connections , To effectively transfer information from the encoder to the decoder . With the support of these two designs ,Uformer High ability to capture useful image recovery dependencies . A large number of experiments on multiple image restoration tasks have proved that Uformer The advantages of , Including image denoising 、 Go to 、 To blur and to dream . We hope that our work will encourage further research , In order to explore low-level visual tasks based on Transformer The architecture of .
Massachusetts institute of technology, | Learning protein language ： evolution , Structure and function
Indian Institute of technology | 2D Comparative semi supervised learning of medical image segmentation
Comparative learning (CL) It's a recent way of expressing learning , It achieves gratifying results by encouraging inter class separability and intra class compactness in learning image representation . Because medical images usually contain multiple categories of interest , So the standard image level of these images CL Do not apply . In this work , We propose a novel semi supervised 2D Medical image segmentation solution , The solution will CL Apply to image blocks , Not the whole picture . these patches It is constructed meaningfully using semantic information of different classes obtained through pseudo tags . We also propose a novel uniform regularization scheme , It works with contrastive learning . It solves the problem of confirmation deviation often observed in semi supervised setup , And encourage better clustering in feature space . We evaluated our approach on four public medical segmented datasets and the new histopathological datasets we introduced . Our method consistently improves the most advanced semi supervised segmentation methods for all datasets .
New developments in machine learning are published again Nature cover ： Solve the problem of medical data privacy
CVPR 2021 Awards come out ： The best papers go to Mapu , He Kaiming was nominated , The first Huang xutao Memorial Award was issued
In recent days, ,CVPR 2021 Published the best paper 、 Best student thesis, etc . Researchers from Marple Institute and tibingen University in Germany won the best paper award , Researchers at Caltech and Northwestern University won the best student thesis Award . Besides ,FAIR Two Chinese scholars, including he Kaiming, were nominated for the best paper , And another Chinese scholar 、 Lin Shanchuan, a graduate student in the Department of computer science at the University of Washington （Shanchuan Lin） Got the best student thesis nomination .
Above is 《 Zhiyuan community AI weekly 》 The first 78 The content of the issue , The editorial team of Zhiyuan Research Institute will be based on “ Provide real experts AI information ” The goal of , Constantly optimize and improve our content services , If you have any criticism , Or good advice , Please point out in the comments section below . Thank you. .
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