Lee

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在没有sudo权限的情况下，在linux上使用clash

Robustness and adaptation of ImageNet scale models. Pre-Release, stay tuned for updates.

关于domain generalization，domain adaptation，causality，robutness，prompt，optimization，generative model各式各样研究的阅读笔记

Sublime Text package to format python code using black formatter.

Black formatter for Sublime Text

calculate yaku and points of japanese mahjong

Blocks specific sites from appearing in Google search results

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The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

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CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

Unofficial Implementation to CDUL: CLIP-Driven Unsupervised Learning for Multi-Label Image Classification [ICCV'23]

:fire: Linux下C++轻量级Web服务器

Official implementation of paper "Contrastively Enforcing Distinctiveness for Multi-label Image Classification"

PyTorch implementation of SimSiam https//arxiv.org/abs/2011.10566

Code for "MixMatch - A Holistic Approach to Semi-Supervised Learning"

Some Conferences' accepted paper lists (including AI, ML, Robotic)

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(Datasets, Transforms and Models specific to Computer Vision)

Contrastive Predictive Coding for Automatic Speaker Verification

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Official PyTorch implementation of the paper "Semantic-Aware Dual Contrastive Learning for Multi-label Image Classification"

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PyTorch implementation of the InfoNCE loss for self-supervised learning.

PyTorch implementation of MoCo: https://arxiv.org/abs/1911.05722

Code for "Towards Effective Visual Representations for Partial-Label Learning" in CVPR 2023.

PyTorch implementation of PiCO https://arxiv.org/abs/2201.08984

C++工程目录结构规范示例

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