Dubbed “the successor to the mobile Internet,” the concept of the Metaverse has grown in
popularity. While there exist lite versions of the Metaverse today, they are still far from …

Since the popularisation of the Internet in the 1990s, the cyberspace has kept evolving. We
have created various computer-mediated virtual environments, including social networks …

State-of-the-art distillation methods are mainly based on distilling deep features from
intermediate layers, while the significance of logit distillation is greatly overlooked. To …

Mainstream 3D representation learning approaches are built upon contrastive or generative
modeling pretext tasks, where great improvements in performance on various downstream …

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 …

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 …

Building general-purpose robots that operate seamlessly in any environment, with any
object, and utilizing various skills to complete diverse tasks has been a long-standing goal in …

The remarkable performance of deep Convolutional neural networks (CNNs) is generally
attributed to their deeper and wider architectures, which can come with significant …

Anomaly detection is a challenging task and usually formulated as an one-class learning
problem for the unexpectedness of anomalies. This paper proposes a simple yet powerful …

Successful integration of deep neural networks (DNNs) or deep learning (DL) has resulted
in breakthroughs in many areas. However, deploying these highly accurate models for data …