Zobrazeno 1 - 10
of 273
pro vyhledávání: '"Gao, Guangwei"'
Optical Coherence Tomography Angiography (OCTA) is a crucial imaging technique for visualizing retinal vasculature and diagnosing eye diseases such as diabetic retinopathy and glaucoma. However, precise segmentation of OCTA vasculature remains challe
Externí odkaz:
http://arxiv.org/abs/2409.08000
In the field of medical microscopic image classification (MIC), CNN-based and Transformer-based models have been extensively studied. However, CNNs struggle with modeling long-range dependencies, limiting their ability to fully utilize semantic infor
Externí odkaz:
http://arxiv.org/abs/2409.07896
Recently, CNN and Transformer hybrid networks demonstrated excellent performance in face super-resolution (FSR) tasks. Since numerous features at different scales in hybrid networks, how to fuse these multi-scale features and promote their complement
Externí odkaz:
http://arxiv.org/abs/2409.00591
Autor:
Xu, Guoan, Huang, Wenfeng, Wu, Tao, Chen, Ligeng, Jia, Wenjing, Gao, Guangwei, Zhu, Xiatian, Perry, Stuart
Semantic segmentation involves assigning a specific category to each pixel in an image. While Vision Transformer-based models have made significant progress, current semantic segmentation methods often struggle with precise predictions in localized a
Externí odkaz:
http://arxiv.org/abs/2408.05699
Both Convolutional Neural Networks (CNNs) and Transformers have shown great success in semantic segmentation tasks. Efforts have been made to integrate CNNs with Transformer models to capture both local and global context interactions. However, there
Externí odkaz:
http://arxiv.org/abs/2407.07441
Autor:
Wang, Zhengxue, Yan, Zhiqiang, Yang, Ming-Hsuan, Pan, Jinshan, Yang, Jian, Tai, Ying, Gao, Guangwei
Multi-modal fusion is vital to the success of super-resolution of depth maps. However, commonly used fusion strategies, such as addition and concatenation, fall short of effectively bridging the modal gap. As a result, guided image filtering methods
Externí odkaz:
http://arxiv.org/abs/2402.13876
Autor:
Li, Wenjie, Wang, Mei, Zhang, Kai, Li, Juncheng, Li, Xiaoming, Zhang, Yuhang, Gao, Guangwei, Deng, Weihong, Lin, Chia-Wen
Face restoration (FR) is a specialized field within image restoration that aims to recover low-quality (LQ) face images into high-quality (HQ) face images. Recent advances in deep learning technology have led to significant progress in FR methods. In
Externí odkaz:
http://arxiv.org/abs/2309.15490
Transformer-based image denoising methods have achieved encouraging results in the past year. However, it must uses linear operations to model long-range dependencies, which greatly increases model inference time and consumes GPU storage space. Compa
Externí odkaz:
http://arxiv.org/abs/2304.06274
Publikováno v:
ICASSP 2023
Stereo image super-resolution aims to boost the performance of image super-resolution by exploiting the supplementary information provided by binocular systems. Although previous methods have achieved promising results, they did not fully utilize the
Externí odkaz:
http://arxiv.org/abs/2303.13807
In the past decade, convolutional neural networks (CNNs) have shown prominence for semantic segmentation. Although CNN models have very impressive performance, the ability to capture global representation is still insufficient, which results in subop
Externí odkaz:
http://arxiv.org/abs/2302.10484