Jizong's Fox's Projects
A2LP for short, ECCV2020 spotlight, Investigating SSL principles for UDA problems
A minimalistic LaTeX template for reports and papers
A painting AI that can reproduce paintings stroke by stroke using deep reinforcement learning.
了凡四訓
Statistical learning methods, 统计学习方法(第2版)[李航] [笔记, 代码, notebook, 参考文献, Errata, lihang]
Python logging made (stupidly) simple
My continuously updated Machine Learning, Probabilistic Models and Deep Learning notes and demos (2000+ slides) 我不间断更新的机器学习,概率模型和深度学习的讲义(2000+页)和视频链接
Encoder-decoder model with attention for batch training.
Machine learning resources
Elegant PyTorch implementation of paper Model-Agnostic Meta-Learning (MAML)
Code of our method MbLS (Margin-based Label Smoothing) for network calibration. To Appear at CVPR 2022. Paper : https://arxiv.org/abs/2111.15430
Reproducibility of Maximum Classifier Discrepancy for Domain Adaptation with Semantic Segmentation
A PyTorch implementation of "MetaFormer: A Unified Meta Framework for Fine-Grained Recognition". A reference PyTorch implementation of “CoAtNet: Marrying Convolution and Attention for All Data Sizes”
Code for "Boosting Semi-supervised Image Segmentation with Global and Local Mutual Information Regularization"
Mirror of the yapf package for pre-commit
Code for "MixMatch - A Holistic Approach to Semi-Supervised Learning"
CVNets: A library for training computer vision networks
More routines for operating on iterables, beyond itertools
Unofficial PyTorch implementation of "Meta Pseudo Labels"
Multi-stream rsync wrapper
Implementation of Multi-View Information Bottleneck
Multimodal Unsupervised Image-to-Image Translation forked for reproduction. High quality work.
A General NeRF Acceleration Toolbox in PyTorch.
A collaboration friendly studio for NeRFs
Code for "MeuMesh: Learning Disentangled Neural Mesh-based Implicit Field for Geometry and Texture Editing", ECCV 2022 Oral
Code release for NeuS
Machine learning, in numpy
Deep Learning Library. For education. Based on pure Numpy. Support CNN, RNN, LSTM, GRU etc.