Highly coherent lasers with spectral hyperpurity can further advance the fields of science and engineering. Especially, a light source with controllable frequency domain parameters can be adapted t…
Weakly supervised semantic segmentation is receiving great attention due to its low human annotation cost. In this paper, we aim to tackle bounding box supervised semantic segmentation, i.e., train…
Object attention maps generated by image classifiers are usually used as priors for weakly supervised semantic segmentation. However, attention maps usually locate the most discriminative object pa…
Cell proliferation, apoptosis, and myosin-dependent contraction can generate elastic stress and strain in living tissues, which may be dissipated by internal rearrangement through cell topological …
Given a natural language expression and an image/video, the goal of referring segmentation is to produce the pixel-level masks of the entities described by the subject of the expression. Previous a…
This paper investigates the principles of embedding learning to tackle the challenging semi-supervised video object segmentation. Unlike previous practices that focus on exploring the embedding lea…
Labeling pixel-level masks for fine-grained semantic segmentation tasks, e.g., human parsing, remains a challenging task. The ambiguous boundary between different semantic parts and those categorie…
As an important supplement to radio frequency (RF) communication in a crowded indoor environment, high-speed multi-user visible light communication (VLC) is a promising candidate for practical appl…
Unsupervised domain adaptation (UDA) makes predictions for the target domain data while manual annotations are only available in the source domain. Previous methods minimize the domain discrepancy …
The meme-centric memetic automaton (MA) was recently proposed as an adaptive entity or a software agent wherein memes are defined as the building blocks of knowledge. The conceptualization of MA ha…