Computer Vision @ Scale
27th April, 2017 11:00 AM
Speaker: Manohar Paluri, research lead at Facebook AI Research, Menlo Park, CA, U.S.A.
Abstract: Over the past 5 years the community has made significant strides in the field of Computer Vision. Thanks to large scale datasets, specialized computing in form of GPUs and many breakthroughs in modeling better ConvNet architectures, Computer Vision systems in the wild at scale are becoming a reality. At Facebook AI Research, we want to embark on the journey of making breakthroughs in the field of AI and using them for the benefit of connecting people and helping remove barriers for communication. In that regard, Computer Vision plays a significant role as the media content coming to Facebook is ever increasing and building models that understand this content is crucial in achieving our mission of connecting everyone. In this talk I will gloss over how we think about problems related to Computer Vision at Facebook and touch various aspects related to supervised, semi-supervised, unsupervised learning. I will jump between various research efforts involving representation learning. I will highlight some large-scale applications that use the technology and talk about limitations of current systems.