Ning Lu's starred repositories
generative-models
Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.
Efficient-AI-Backbones
Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.
PyTorch-StudioGAN
StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.
webdataset
A high-performance Python-based I/O system for large (and small) deep learning problems, with strong support for PyTorch.
OS-Copilot
An self-improving embodied conversational agent seamlessly integrated into the operating system to automate our daily tasks.
awesome-attention-mechanism-in-cv
Awesome List of Attention Modules and Plug&Play Modules in Computer Vision
Switchable-Normalization
Code for Switchable Normalization from "Differentiable Learning-to-Normalize via Switchable Normalization", https://arxiv.org/abs/1806.10779
WeightStandardization
Standardizing weights to accelerate micro-batch training
annotated-mamba
Annotated version of the Mamba paper
MultiModalMamba
A novel implementation of fusing ViT with Mamba into a fast, agile, and high performance Multi-Modal Model. Powered by Zeta, the simplest AI framework ever.
Personal_LLM_Agents_Survey
Paper list for Personal LLM Agents
awesome-normalization-techniques
Papers for normalization techniques, released codes collections.
PIMoG-An-Effective-Screen-shooting-Noise-Layer-Simulation-for-Deep-Learning-Based-Watermarking-Netw
This is the code for paper: ``PIMoG : An Effective Screen-shooting Noise-Layer Simulation for Deep-Learning-Based Watermarking Network. .Fang, Han, et al. Proceedings of the 30th ACM International Conference on Multimedia. 2022.
A-Novel-Two-stage-Separable-Deep-Learning-Framework-for-Practical-Blind-Watermarking
The codes for the paper "A Novel Two-stage Separable Deep Learning Framework for Practical Blind Watermarking"
differentiable-jpeg
Code for "JPEG-resistant Adversarial Images"