10 Cutting-Edge Research Papers In Computer Vision From 2019

Today we can see how computer vision (CV) systems are revolutionizing whole industries and business functions with successful applications in healthcare, security, transportation, retail, banking, agriculture, and more. In 2019, we saw lots of novel architectures and approaches that further improved the perceptive and generative capacities of visual systems. To help you navigate through the overwhelming number of great computer vision papers presented this year, we've curated and summarized the top 10 CV research papers of 2019 that will help you understand the latest trends in this research area. The papers that we selected cover optimization of convolutional networks, unsupervised learning in computer vision, image generation and evaluation of machine-generated images, visual-language navigation, captioning changes between two images with natural language, and more. Subscribe to our AI Research mailing list at the bottom of this article to be alerted when we release new summaries. If you'd like to skip around, here are the papers we featured: Convolutional Neural Networks (ConvNets) are commonly developed at a fixed resource budget, and then scaled up for better accuracy if more resources are available.