Lists (8)
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AIGC
用于收藏生成式模型相关仓库dataset
deep learning topics summary
DETR based Detection
DETR相关算法interesting project
learning materials
books, websites for learning program, AI and IT knowledgepractical toolbox
X2CT related work
X光生成CT相关工作Stars
[CVPR 2022 Oral] Official implementation of DN-DETR
LPIPS metric. pip install lpips
The official pytorch implemention of our ICML-2021 paper "SimAM: A Simple, Parameter-Free Attention Module for Convolutional Neural Networks".
An ultimately comprehensive paper list of Vision Transformer/Attention, including papers, codes, and related websites
《Pytorch实用教程》(第二版)无论是零基础入门,还是CV、NLP、LLM项目应用,或是进阶工程化部署落地,在这里都有。相信在本书的帮助下,读者将能够轻松掌握 PyTorch 的使用,成为一名优秀的深度学习工程师。
Free Introduction to Git and GitHub eBook
Ensembling Off-the-shelf Models for GAN Training (CVPR 2022 Oral)
Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.
Image-to-image translation with conditional adversarial nets
Generative Models by Stability AI
Collection of generative models in Pytorch version.
PyTorch package for the discrete VAE used for DALL·E.
A Collection of Variational Autoencoders (VAE) in PyTorch.
One-step image-to-image with Stable Diffusion turbo: sketch2image, day2night, and more
Image-to-Image Translation in PyTorch
A collection of resources and papers on Diffusion Models
A MNIST-like fashion product database. Benchmark 👇
detrex is a research platform for DETR-based object detection, segmentation, pose estimation and other visual recognition tasks.
[ICLR 2023] Official implementation of the paper "DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection"
[TPAMI 2022 & CVPR2021 Oral] UP-DETR: Unsupervised Pre-training for Object Detection with Transformers
End-to-End Object Detection with Transformers
Deformable DETR: Deformable Transformers for End-to-End Object Detection.
[CVPR'2022] SAM-DETR & SAM-DETR++: Official PyTorch Implementation
A curated list of awesome Deep Learning tutorials, projects and communities.
深度学习入门教程, 优秀文章, Deep Learning Tutorial
深度学习500问,以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述,以帮助自己及有需要的读者。 全书分为18个章节,50余万字。由于水平有限,书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作,联系[email protected] 版权所有,违权必究 Tan 2018.06
An opinionated list of awesome Python frameworks, libraries, software and resources.
⏰ Collaboratively track deadlines of conferences recommended by CCF (Website, Python Cli, Wechat Applet) / If you find it useful, please star this project, thanks~