Vector Quantisation (VQ) is experiencing a comeback in machine learning, where it is
increasingly used in representation learning. However, optimizing the codevectors in …

Abstract Although two-stage Vector Quantized (VQ) generative models allow for
synthesizing high-fidelity and high-resolution images, their quantization operator encodes …

The goal of image rescaling is to embed the information from high-resolution images into
low-resolution images and then reconstruct the high-resolution images in reverse. Existing …

Image restoration is a prominent field of research in computer vision. Restoring broken
paintings, especially ancient Chinese artworks, is a significant challenge for current …

Vanilla image completion approaches exhibit sensitivity to large missing regions, attributed
to the limited availability of reference information for plausible generation. To mitigate this …

Vanilla image completion approaches exhibit sensitivity to large missing regions, attributed
to the limited availability of reference information for plausible generation. To mitigate this …

Background: The lack of wildfire smoke image data is one of the most important factors
hindering the development of image-based wildfire detection. Smoke image generation …

Vision tokenizers have gained a lot of attraction due to their scalability and compactness;
previous works depend on old-school GAN-based hyperparameters, biased comparisons …

Thangka, as a precious heritage of painting art, holds irreplaceable research value due to its
richness in Tibetan history, religious beliefs, and folk culture. However, it is susceptible to …

深度学**的快速发展使计算机视觉技术应用越来越广泛, 同时利用深度神经网络根据破损图像的
已知信息对图像复原的修复技术成为关注的热点. 对**年基于深度神经网络的图像修复方法进行 …