In recent years, deep neural networks have been successful in both industry and academia,
especially for computer vision tasks. The great success of deep learning is mainly due to its …

Abstract Knowledge distillation is a widely used paradigm for inheriting information from a
complicated teacher network to a compact student network and maintaining the strong …

Object detection (OD) is a crucial computer vision task that has seen the development of
many algorithms and models over the years. While the performance of current OD models …

Semantic scene understanding using thermal images has received great attention due to the
advantage that thermal imaging cameras could see in challenging illumination conditions …

摘要在人工智能迅速发展的今天, 深度神经网络广泛应用于各个研究领域并取得了巨大的成功,
但也同样面临着诸多挑战. 首先, 为了解决复杂的问题和提高模型的训练效果 …

In the last decade, many deep learning models have been well trained and made a great
success in various fields of machine intelligence, especially for computer vision and natural …

The recent advancement in vision-and-language pretraining (VLP) has significantly
improved the performance of cross-modal image-text retrieval (ITR) systems. However, the …

Target detection is a revolutionary advancement in computer vision that provides the ability
to identify specific targets in images for a wide variety of applications, including but not …

Efficient visual detection is a crucial component in self-driving perception and lays the
foundation for later planning and control stages. Deep-networks-based visual systems …

The knowledge of a well-trained deep neural network (aka the “teacher”) is valuable for
learning similar tasks. Knowledge distillation extracts knowledge from the teacher and …