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Starred repositories
JavaScript syntax highlighter with language auto-detection and zero dependencies.
🌐 Jekyll is a blog-aware static site generator in Ruby
[CVPR 2022] Aesthetic Text Logo Synthesis via Content-aware Layout Inferring
OpenMMLab Text Detection, Recognition and Understanding Toolbox
Python package for reading Adobe Photoshop PSD files
A very fast and expressive template engine.
ICML'20: SIGUA: Forgetting May Make Learning with Noisy Labels More Robust
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
A cleaned version of IMDB-WIKI dataset for facial age estimation.
ICLR‘2021: Robust Early-learning: Hindering the Memorization of Noisy Labels
This is the official repo for our CVPR22 paper: Scalable Penalized Regression for Noise Detection in Learning With Noisy Labels.
Pyroomacoustics is a package for audio signal processing for indoor applications. It was developed as a fast prototyping platform for beamforming algorithms in indoor scenarios.
NeurIPS'18: Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels
A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques
📄 Awesome CV is LaTeX template for your outstanding job application
[CVPR 2024 Highlight] Style Injection in Diffusion: A Training-free Approach for Adapting Large-scale Diffusion Models for Style Transfer
Official implementation of the paper “Inversion-Based Style Transfer with Diffusion Models” (CVPR 2023)
GIT: A Generative Image-to-text Transformer for Vision and Language
Image to prompt with BLIP and CLIP
ArtGAN + WikiArt: This work presents a series of new approaches to improve GAN for conditional image synthesis and we name the proposed model as “ArtGAN”.
StyleShot: A SnapShot on Any Style. 一款可以迁移任意风格到任意内容的模型，无需针对图片微调，即能生成高质量的个性风格化图片!
Dataset to assess the disentanglement properties of unsupervised learning methods
PyTorch implementation of "Supervised Contrastive Learning" (and SimCLR incidentally)