In this tutorial paper, we look into the evolution and prospect of network architecture and
propose a novel conceptual architecture for the 6th generation (6G) networks. The proposed …

As an emerging and challenging problem in the computer vision community, weakly
supervised object localization and detection plays an important role for develo** new …

For years, the YOLO series has been the de facto industry-level standard for efficient object
detection. The YOLO community has prospered overwhelmingly to enrich its use in a …

As camera and LiDAR sensors capture complementary information in autonomous driving,
great efforts have been made to conduct semantic segmentation through multi-modality data …

Abstract Knowledge distillation has been applied to image classification successfully.
However, object detection is much more sophisticated and most knowledge distillation …

Abstract Knowledge distillation aims to compress a powerful yet cumbersome teacher model
into a lightweight student model without much sacrifice of performance. For this purpose …

Abstract Knowledge distillation has been applied to various tasks successfully. The current
distillation algorithm usually improves students' performance by imitating the output of the …

The representation gap between teacher and student is an emerging topic in knowledge
distillation (KD). To reduce the gap and improve the performance, current methods often …

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 …

Vision-language models trained with contrastive learning on large-scale noisy data are
becoming increasingly popular for zero-shot recognition problems. In this paper we improve …