Today's scene graph generation (SGG) task is largely limited in realistic scenarios, mainly
due to the extremely long-tailed bias of predicate annotation distribution. Thus, tackling the …

Enlarging input images is a straightforward and effective approach to promote small object
detection. However, simple image enlargement is significantly expensive on both …

Based on the framework of multiple instance learning (MIL), tremendous works have
promoted the advances of weakly supervised object detection (WSOD). However, most MIL-based …

Detecting objects in surveillance videos is an important problem due to its wide applications
in traffic control and public security. Existing methods tend to face performance degradation …

Without manually annotated identities, unsupervised multi-object trackers are inferior to
learning reliable feature embeddings. It causes the similarity-based inter-frame association …

Functional connectivity measured from resting state fMRI (R-fMRI) data has been widely used
to examine the brain’s functional activities and has been recently used to characterize and …

In consideration of secure and convenient, face gains increasing attention in variety of fields
during the past decades. Since human face is most accessible from our daily life and …

Pneumonia remains a threat to human health; the coronavirus disease 2019 (COVID‐19)
that began at the end of 2019 had a major impact on the world. It is still raging in many …

Person re-identification (re-ID), which aims at spotting a person of interest across multiple
camera views, has gained more and more attention in computer vision community. In this paper…

When reading long-form text, human cognition is complex and structurized. While large
language models (LLMs) process input contexts through a causal and sequential perspective, …