Despite the promising progress made in recent years, person re-identification remains a
challenging task due to complex variations in human appearances from different camera …

We propose a technique that tackles action detection in multimodal videos under a realistic
and challenging condition in which only limited training data and partially observed …

Unlike machines, humans learn through rapid, abstract model-building. The role of a teacher
is not simply to hammer home right or wrong answers, but rather to provide intuitive …

Multiview learning (MVL), by exploiting the complementary information among multiple
feature sets, can improve the performance of many existing learning tasks. Support vector …

Quasi-static ultrasound elastography is an importance imaging technology to assess the
conditions of various diseases through reconstructing the tissue strain from radio frequency …

Equipping machine learning models with ethical and legal constraints is a serious issue;
without this, the future of machine learning is at risk. This paper takes a step forward in this …

In school, a teacher plays an important role in various classroom teaching patterns. Likewise
to this human learning activity, the learning using privileged information (LUPI) paradigm …

Existing RNN-based approaches for action recognition from depth sequences require either
skeleton joints or hand-crafted depth features as inputs. An end-to-end manner, mapping …

We study human pose estimation in extremely low-light images. This task is challenging due
to the difficulty of collecting real low-light images with accurate labels, and severely …

We explore the visual recognition problem from a main data view when an auxiliary data
view is available during training. This is important because it allows improving the training of …