CVPR 2024 真实超分 SeeSR: Towards Semantics-Aware Real-World Image Super-Resolution 星晴 AIGC72 人赞同了该文章 arxiv:arxiv.org/pdf/2311.1651 港理工张磊的又一个新作,将包含语义信息的Prompts用于真实超分 Motivation 由于退化会导致局部结构的破坏和语义信息的模糊,text-to-image (T2I) diffusion models...
【ICLR 2024】Recursive Generalization Transformer For Image Super-Resolution 苍梧 程序员1 人赞同了该文章 论文解决的问题 问题提出:传统的Transformer架构在图像超分辨率(SR)任务中表现出色,但其自注意力(SA)机制的计算复杂度随着图像尺寸的增加而呈二次方增长。为了降低计算开销,现有方法通常只在局部区域内使用SA,...
ImageSuperResolution superResolution = new ImageSuperResolution(mContext); Frame frame = new Frame(); frame.setBitmap(bitmap); ImageResult result = superResolution.doSuperResolution(frame, null); Bitmap resultBitmap = result.getBitmap(); ...
[5] Chu, Xiaojie, Liangyu Chen, and Wenqing Yu. “NAFSSR: Stereo image super-resolution using NAFNet.” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2022. [6] Chen, Xiangyu, et al. “Activating more pixels in image super-resolution transformer.” Procee...
This repository includes the official implementation of the paperAdaBM: On-the-Fly Adaptive Bit Mapping for Image Super-Resolution(CVPR2024). Requirements A suitablecondaenvironment namedadabmcan be created and activated with: conda env create -f environment.yaml conda activate adabm ...
【摘要】 图像超分辨率(Image Super-resolution)1. 引言图像超分辨率(Image Super-resolution)是一项重要的图像处理技术,旨在通过算法和模型将低分辨率图像提升到高分辨率,从而增强图像的细节和清晰度。随着高清晰度显示设备的普及和对图像质量要求的提高,图像超分辨率技术在数字图像处理、计算机视觉和人工智能领域受到了广泛...
SeeSR: Towards Semantics-Aware Real-World Image Super-Resolution (CVPR2024) Rongyuan Wu1,2 | Tao Yang3 | Lingchen Sun1,2 | Zhengqiang Zhang1,2 | Shuai Li1,2 | Lei Zhang1,2 1The Hong Kong Polytechnic University, 2OPPO Research Institute, 3ByteDance Inc. ⭐ If SeeSR is helpful to...
ActionString是GenerateSuperResolutionImage 系统规定参数。取值:GenerateSuperResolutionImage。 ImageUrlString是https://viapi-test.oss-cn-shanghai.aliyuncs.com/test/xxx/1025.jpg 输入图片地址。推荐使用上海地域的OSS链接,对于文件在本地或者非上海地域OSS链接的情况,请参见文件URL处理。
To better extract detailed features and enhance the cascading effects of different feature levels, we propose a novel medical image super-resolution algorithm that integrates discrete wavelet transform and multi-scale adaptive feature selection. Our approach uses both the low-resolution image and its ...
作者指出,当前基于Transformer的超分辨率方法,需要在窗口里面计算注意力,但是窗口大了计算复杂度高,窗口小了感受野不够。为此作者提出了 HiT-SR 方法,分别在 block level 和 layer level 进行了改进(下图中…