Image classification has always been a hot research direction in the world, and the
emergence of deep learning has promoted the development of this field. Convolutional …

Deep learning has received extensive research interest in develo** new medical image
processing algorithms, and deep learning based models have been remarkably successful …

Recently the state space models (SSMs) with efficient hardware-aware designs, ie, the
Mamba deep learning model, have shown great potential for long sequence modeling …

Abstract We present CSWin Transformer, an efficient and effective Transformer-based
backbone for general-purpose vision tasks. A challenging issue in Transformer design is …

Although convolutional neural networks (CNNs) have achieved great success in computer
vision, this work investigates a simpler, convolution-free backbone network useful for many …

For machine learning systems to be reliable, we must understand their performance in
unseen, out-of-distribution environments. In this paper, we empirically show that out-of …

Blind face restoration usually relies on facial priors, such as facial geometry prior or
reference prior, to restore realistic and faithful details. However, very low-quality inputs …

Boundary discontinuity and its inconsistency to the final detection metric have been the
bottleneck for rotating detection regression loss design. In this paper, we propose a novel …

Recently, Vision Transformers (ViTs) have been broadly explored in visual recognition. With
low efficiency in encoding fine-level features, the performance of ViTs is still inferior to the …

Deep learning's recent history has been one of achievement: from triumphing over humans
in the game of Go to world-leading performance in image classification, voice recognition …