【论文题目】Spatially-Adaptive Feature Modulation for Efficient Image Super-Resolution 【出处】ICCV 2023 南京理工大学的工作,今年在low-level任务上南理工还有另一个工作DLGSANet,回头我再梳理一下这篇文章。 【原文链接】(代码已开源) arxiv.org/pdf/2302.13800.pdfarxiv.org/pdf/2302.13800.pdf 导读 本...
论文链接:Spatially-Adaptive Feature Modulation for Efficient Image Super-Resolution 代码链接:github 摘要 在本文中,提出了一个简单而有效的深度网络来解决图像超分辨率。详细来说,在一个类似ViT的模块上,开发了一个空间自适应特征调制(SAFM)机制。在这个机制中,我们首先在输入特征上应用SAFM模块,动态地选择有代表性...
📖 Spatially-Adaptive Feature Modulation for Efficient Image Super-Resolution [Paper] [Supp] Long Sun,Jiangxin Dong,Jinhui Tang, andJinshan Pan IMAG Lab, Nanjing University of Science and Technology An overview of the proposed SAFMN. SAFMN first transforms the input LR image into the feat...
Single Image Super-Resolution via Adaptive High-Dimensional Non-Local Total Variation and Adaptive Geometric Feature Single image super-resolution (SR) is very important in many computer vision systems. However, as a highly ill-posed problem, its performance mainly relies... C Ren,X He,T Nguyen...
This repository is the implementation of"Variable-Rate Deep Image Compression through Spatially-Adaptive Feature Transform"(ICCV 2021). Our code is based onCompressAI. Abstract:We propose a versatile deep image compression network based on Spatial Feature Transform (SFT), which takes a source image ...
代码:https://github.com/zdaxie/SpatiallyAdaptiveInference-Detection 这个论文的关键词是动态网络。如下图所示,动态网络目标是可以对 简单 和困难 的样本分别 采用不同的网络进行推理。对于简单样本采用小网络,对于困难样本采用大网络,这样可以有效降低计算中的冗余。 这篇论文就是研究动态网络,只对输入feature map部...
Towards reducing this superfluous computation, we propose to compute features only at sparsely sampled locations, which are probabilistically chosen according to activation responses, and then densely reconstruct the feature map with an efficient interpolation procedure. With this sampling-interpolation scheme...
This feature makes it difficult to directly apply existing algorithms and take advantage of the event camera data. Due to the developments in neural networks, important advances were made in event-based image reconstruction. Even though these neural networks achieve precise reconstructions while ...
(2007). Subband-Adaptive and Spatially-Adaptive Wavelet Thresholding for Denoising and Feature Preservation of Texture Images. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2007. Lecture Notes in Computer Science, vol 4633. Springer, Berlin, Heidelberg. https://doi....
我们看到,整个网络结构是先生成一列学习好的数据分布,然后通过一层一层的SPADE ResBlk堆叠而成,feature map尺寸由小到大,通道数由大到小来生成最终的真实图片的。而在每一层SPADE ResBlk中,不断地加入语义分割图片来进行干预,这样可以让网络在每一层都能学习到多尺度的语义信息。 每一个SPADE ResBlk又是由SPADE...