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Kang341281X
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一个基于 vue、datav、Echart 框架的大数据可视化（大屏展示）模板，实现大数据可视化。通过 vue 组件实现数据动态刷新渲染，内部图表可自由替换。部分图表使用 DataV 自带组件，可自由进行更改（ps：最新的更新请前往码云查看，下面有链接）。
数据可视化大屏电子沙盘集合，基于：HTML/CSS/Echarts等等，包含行业：区块链金融行业、智慧社区、智慧物业、智慧政务、智慧交通、通用模板等，包含功能：自定义字体、Css动画、WebSocket实时数据、K线折线等各种图表，iframe嵌套H5/App，替换js数据即可，满足您会议展览、业务监控、风险预警、数据分析展示等多种展示需求🔝 右上角点个 Star 关注更新，笔芯
PyTorch implementation of the TIP2017 paper "Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising"
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising (TIP, 2017)
Official PyTorch Implementation of "Scalable Diffusion Models with Transformers"
Official pytorch implementation of the paper: "SinDDM: A Single Image Denoising Diffusion Model"
PyTorch implementation of "Deep Equilibrium Diffusion Restoration with Parallel Sampling (CVPR 2024)"
CVPR2024 - Transcending the Limit of Local Window: Advanced Super-Resolution Transformer with Adaptive Token Dictionary
[CVPR 2024] SinSR: Diffusion-Based Image Super-Resolution in a Single Step
Official implementation of Inf-DiT: Upsampling Any-Resolution Image with Memory-Efficient Diffusion Transformer
[ICCV 2023] Learning Correction Filter via Degradation-Adaptive Regression for Blind Single Image Super-Resolution
Self-Supervised Scalable Deep Compressed Sensing (IJCV 2024) [PyTorch]
Color BSD68 dataset for image denoising benchmarks
Dual residual attention network for image denoising (Pattern Recognition, 2024)
Multi-platform auto-proxy client, supporting Sing-box, X-ray, TUIC, Hysteria, Reality, Trojan, SSH etc. It’s an open-source, secure and ad-free.
A toolbox for spectral compressive imaging reconstruction including MST (CVPR 2022), CST (ECCV 2022), DAUHST (NeurIPS 2022), BiSCI (NeurIPS 2023), HDNet (CVPR 2022), MST++ (CVPRW 2022), etc.
Code implementation and dataset of <<CNN-based Prediction of Partition Path for VVC Fast Inter Partitioning Using Motion Fields>>
A large-scale database for QTMT-based CU partition of VVC.
The official project website of "Dynamic Mobile-Former: Strengthening Dynamic Convolution with Attention and Residual Connection in Kernel Space".
Deformable Convolutional Networks v2 with Pytorch