In he past decade, object detection has achieved significant progress in natural images but
not in aerial images, due to the massive variations in the scale and orientation of objects …

We build new test sets for the CIFAR-10 and ImageNet datasets. Both benchmarks have
been the focus of intense research for almost a decade, raising the danger of overfitting to …

Object detection is an important and challenging problem in computer vision. Although the
past decade has witnessed major advances in object detection in natural scenes, such …

Action recognition has typically treated actions and activities as monolithic events that occur
in videos. However, there is evidence from Cognitive Science and Neuroscience that people …

Despite progress in perceptual tasks such as image classification, computers still perform
poorly on cognitive tasks such as image description and question answering. Cognition is …

Abstract The ImageNet Large Scale Visual Recognition Challenge is a benchmark in object
category classification and detection on hundreds of object categories and millions of …

This paper develops a novel framework for semantic image retrieval based on the notion of
a scene graph. Our scene graphs represent objects (" man"," boat"), attributes of objects (" …

This paper aims to conduct a comprehensive study on facial-sketch synthesis (FSS).
However, due to the high cost of obtaining hand-drawn sketch datasets, there is a lack of a …

Accurately estimating the number of objects in a single image is a challenging yet
meaningful task and has been applied in many applications such as urban planning and …

Existing enhancement methods are empirically expected to help the high-level end
computer vision task: however, that is observed to not always be the case in practice. We …