Recently, efficient fine-tuning of large-scale pre-trained models has
at...
Predicting attention regions of interest is an important yet challenging...
In recent years, there has been an increased popularity in image and spe...
Infrared and visible image fusion can compensate for the incompleteness ...
Image-based head swapping task aims to stitch a source head to another s...
Speech representation learning has improved both speech understanding an...
Multi-view learning has progressed rapidly in recent years. Although man...
Semantic segmentation with limited annotations, such as weakly supervise...
Due to the lack of expertise for medical image annotation, the investiga...
Open-domain Question Answering (ODQA) has achieved significant results i...
Crowd counting on the drone platform is an interesting topic in computer...
To promote the developments of object detection, tracking and counting
a...
Semantic parsing has long been a fundamental problem in natural language...
Although significant progress achieved, multi-label classification is st...
Unsupervised domain adaptation is critical in various computer vision ta...
The convention standard for object detection uses a bounding box to repr...
Drone equipped with cameras can dynamically track the target in the air ...
Multi-choice Machine Reading Comprehension (MRC) requires model to decid...
Drones, or general UAVs, equipped with cameras have been fast deployed w...
This paper proposes a space-time multi-scale attention network (STANet) ...
Channel attention has recently demonstrated to offer great potential in
...
Multi-view subspace clustering aims to discover the inherent structure b...
Along with the deraining performance improvement of deep networks, their...
This paper reviews the first challenge on efficient perceptual image
enh...
Traditional chatbots usually need a mass of human dialogue data, especia...
Machine reading comprehension is a task to model relationship between pa...
Multi-turn conversation understanding is a major challenge for building
...
In this paper we present a large-scale visual object detection and track...
Deep Reinforcement Learning (RL) recently emerged as one of the most
com...
With the rapid development of digital imaging and communication technolo...