In this paper, we consider a real-world scenario where a model that is
t...
Visible-Infrared person Re-IDentification (VI-ReID) is a challenging
cro...
Multi-label image recognition aims to predict a set of labels that prese...
Most previous learning-based graph matching algorithms solve the
quadrat...
Differentiable solvers for the linear assignment problem (LAP) have attr...
In this work, we focus on Interactive Human Parsing (IHP), which aims to...
Visible-infrared cross-modality person re-identification is a challengin...
Multi-Label Image Classification (MLIC) aims to predict a set of labels ...
With the aim of matching a pair of instances from two different modaliti...
In the past few decades, to reduce the risk of X-ray in computed tomogra...
Partial Label Learning (PLL) aims to learn from the data where each trai...
Person re-identification (Re-ID) across multiple datasets is a challengi...
Partial Label Learning (PLL) aims to learn from the data where each trai...
Partial label learning (PLL) aims to solve the problem where each traini...