Detecting objects remains one of computer vision and image understanding applications'
most fundamental and challenging aspects. Significant advances in object detection have …

Tiny object detection is one of the challenges in the field of object detection, which can be
applied in a variety of fields. Thanks to the advances in deep learning, significant …

There are a huge number of features which are said to improve Convolutional Neural
Network (CNN) accuracy. Practical testing of combinations of such features on large …

Neural networks have enabled state-of-the-art approaches to achieve incredible results on
computer vision tasks such as object detection. However, such success greatly relies on …

Object detection has been dominated by anchor-based detectors for several years.
Recently, anchor-free detectors have become popular due to the proposal of FPN and Focal …

Single-stage instance segmentation approaches have recently gained popularity due to
their speed and simplicity, but are still lagging behind in accuracy, compared to two-stage …

Multimodal named entity recognition and relation extraction (MNER and MRE) is a
fundamental and crucial branch in information extraction. However, existing approaches for …

Understanding interactions between humans and objects is one of the fundamental
problems in visual classification and an essential step towards detailed scene …

We propose a novel two-stage detection method, D2Det, that collectively addresses both
precise localization and accurate classification. For precise localization, we introduce a …

As one of the most important defects of concrete, cracks seriously threaten the service life
and safety of concrete structures, and various safety incidents caused by the collapse of …