Researchers are defining new types of interactions between humans and machine learning
algorithms generically called human-in-the-loop machine learning. Depending on who is in …

Curriculum learning (CL) is a training strategy that trains a machine learning model from
easier data to harder data, which imitates the meaningful learning order in human curricula …

As an emerging and challenging problem in the computer vision community, weakly
supervised object localization and detection plays an important role for developing new …

In recent years, weakly supervised object detection has attracted great attention in the
computer vision community. Although numerous deep learning-based approaches have …

Recently, video object segmentation has received great attention in the computer vision
community. Most of the existing methods heavily rely on the pixel-wise human annotations …

Weakly supervised object localization (WSOL) aims at learning to localize objects of interest
by only using the image-level labels as the supervision. While numerous efforts have been …

With the goal of learning to localize specific object semantics using the low-cost image-level
annotation, weakly supervised object localization (WSOL) has been receiving increasing …

In this paper, we study the fine-grained categorization problem under the few-shot setting, ie,
each fine-grained class only contains a few labeled examples, termed Fine-Grained Few …

CCTV cameras installed for continuous surveillance generate enormous amounts of data
daily, forging the term Big Video Data (BVD). The active practice of BVD includes intelligent …

Co-Saliency Detection (CSD) is to explore the concurrent patterns and salient objects from a
group of relevant images, while Instance Co-Segmentation (ICS) aims to identify and …