Electronic skins (e-skins) have seen intense research and rapid development in the past two
decades. To mimic the capabilities of human skin, a multitude of flexible/stretchable sensors …

This paper reviews the NTIRE 2023 challenge on image super-resolution (x4), focusing on
the proposed solutions and results. The task of image super-resolution (SR) is to generate a …

To design fast neural networks, many works have been focusing on reducing the number of
floating-point operations (FLOPs). We observe that such reduction in FLOPs, however, does …

Abstract Convolutional Neural Networks (CNNs) have achieved remarkable performance in
various computer vision tasks but this comes at the cost of tremendous computational …

Image restoration aims to reconstruct a sharp image from its degraded counterpart, which
plays an important role in many fields. Recently, Transformer models have achieved …

In this paper, we study Multiscale Vision Transformers (MViTv2) as a unified architecture for
image and video classification, as well as object detection. We present an improved version …

Recent studies show that transformer has strong capability of building long-range
dependencies, yet is incompetent in capturing high frequencies that predominantly convey …

Abstract Vision Transformers (ViTs) have triggered the most recent and significant
breakthroughs in computer vision. Their efficient designs are mostly guided by the indirect …

In this paper, we propose a conceptually simple but very effective attention module for
Convolutional Neural Networks (ConvNets). In contrast to existing channel-wise and spatial …

Abstract We present Multiscale Vision Transformers (MViT) for video and image recognition,
by connecting the seminal idea of multiscale feature hierarchies with transformer models …