DNNs have shown remarkable success in many computer vision and machine learning tasks. Despite a wide range of impressive results, current DNN based methods typically depend on massive amounts of accurately annotated training data to achieve high performance. DNNs lack the ability of learning from limited exemplars and fast generalizing to new tasks.
The Visual Intelligence Group in School of Data Science, Fudan University will hold the 1st Visual Intelligence Seminar on Few-shot Learning on January 29, 2021. We invite several distinguished speakers to share the recent progress on few-shot learning.