资源论文Human Activity Recognition with Metric Learning

Human Activity Recognition with Metric Learning

2020-03-30 | |  48 |   29 |   0

Abstract

This paper proposes a metric learning based approach for human activity recognition with two main ob jectives: (1) reject unfa- miliar activities and (2) learn with few examples. We show that our approach outperforms all state-of-the-art methods on numerous stan- dard datasets for traditional action classification problem. Furthermore, we demonstrate that our method not only can accurately label activities but also can reject unseen activities and can learn from few examples with high accuracy. We finally show that our approach works well on noisy YouTube videos.

上一篇:Efficient Dense Scene Flow from Sparse or Dense Stereo Data

下一篇:SMD: A Locally Stable Monotonic Change Invariant Feature Descriptor

用户评价
全部评价

热门资源

  • Learning to Predi...

    Much of model-based reinforcement learning invo...

  • Stratified Strate...

    In this paper we introduce Stratified Strategy ...

  • The Variational S...

    Unlike traditional images which do not offer in...

  • A Mathematical Mo...

    Direct democracy, where each voter casts one vo...

  • Rating-Boosted La...

    The performance of a recommendation system reli...