技能目录

为 AI Agent 发现可复用技能。

按任务搜索真实的 GitHub 技能,并在使用前查看 Stars、信任、审计、分类和安装路径。

每个推荐都保留与其仓库、审计和安装路径的明确关联。

搜索结果: denoising

英文目录

MuseV: Infinite-length and High Fidelity Virtual Human Video Generation with Visual Conditioned Parallel Denoising

2.8K
Stars
68/100
信任
分类: media-automation审计

[ICLR 2023] Official implementation of the paper "DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection"

2.8K
Stars
72/100
信任
分类: robotics-iot审计

[CVPR 2021] Multi-Stage Progressive Image Restoration. SOTA results for Image deblurring, deraining, and denoising.

1.4K
Stars
68/100
信任
分类: robotics-iot审计

[ECCV 2020] Learning Enriched Features for Real Image Restoration and Enhancement. SOTA results for image denoising, super-resolution, and image enhancement.

721
Stars
62/100
信任
分类: robotics-iot审计

A list of resources for video enhancement, including video super-resolutio, interpolation, denoising, compression artifact removal et al..

599
Stars
62/100
信任
分类: media-automation审计

[AAAI2024] FontDiffuser: One-Shot Font Generation via Denoising Diffusion with Multi-Scale Content Aggregation and Style Contrastive Learning

528
Stars
62/100
信任
分类: media-automation审计

Person Image Synthesis via Denoising Diffusion Model (CVPR 2023)

503
Stars
63/100
信任
分类: media-automation审计

A minimal implementation of a denoising diffusion model in PyTorch.

134
Stars
65/100
信任
分类: media-automation审计

Several image/video enhancement methods, implemented by Java, to tackle common tasks, like dehazing, denoising, backscatter removal, low illuminance enhancement, featuring, smoothing and etc.

496
Stars
63/100
信任
分类: media-automation审计

Medical Diffusion: This repository contains the code to our paper Medical Diffusion: Denoising Diffusion Probabilistic Models for 3D Medical Image Synthesis

493
Stars
59/100
信任
分类: ml-automation审计

PyTorch Implementation of DiffGAN-TTS: High-Fidelity and Efficient Text-to-Speech with Denoising Diffusion GANs

349
Stars
62/100
信任
分类: media-automation审计

A simple guide to diffusion models. Helpful in understanding the concept and practicing with the method.

224
Stars
59/100
信任
分类: robotics-iot审计