Backpropagation algorithm has been widely used as a mainstream learning
...
Collaborative perception is essential to address occlusion and sensor fa...
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...
The RGB-infrared cross-modality person re-identification (ReID) task aim...
In recent years, powered by the learned discriminative representation vi...
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...
Feature pyramid network (FPN) based models, which fuse the semantics and...
Partial Label Learning (PLL) aims to learn from the data where each trai...
Person re-identification (Re-ID) across multiple datasets is a challengi...
To detect and segment salient objects accurately, existing methods are
u...
Partial Label Learning (PLL) aims to learn from the data where each trai...
The recent progress of human parsing techniques has been largely driven ...