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Zhongjianmei's Projects

aflow icon aflow

Official PyTorch Implementation of "AFlow: Alternating Normalizing Flow for Unsupervised Anomaly Detection and Localization"

ano_pred_cvpr2018 icon ano_pred_cvpr2018

Official implementation of Paper Future Frame Prediction for Anomaly Detection -- A New Baseline, CVPR 2018

anomalib icon anomalib

An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.

auto-gpt icon auto-gpt

An experimental open-source attempt to make GPT-4 fully autonomous.

bgad icon bgad

Pytorch Implementation for CVPR2023 paper: Explicit Boundary Guided Semi-Push-Pull Contrastive Learning for Supervised Anomaly Detection

blog icon blog

Public repo for HF blog posts

cdo icon cdo

[TII 2023] Collaborative Discrepancy Optimization for Reliable Image Anomaly Localization

cflow-ad icon cflow-ad

Official PyTorch code for WACV 2022 paper "CFLOW-AD: Real-Time Unsupervised Anomaly Detection with Localization via Conditional Normalizing Flows"

chatglm-6b icon chatglm-6b

ChatGLM-6B:开源双语对话语言模型 | An open bilingual dialogue language model

chatgpt_academic icon chatgpt_academic

科研工作专用ChatGPT拓展,特别优化学术Paper润色体验,支持自定义快捷按钮,支持markdown表格显示,Tex公式双显示,代码显示功能完善,新增本地Python工程剖析功能/自我剖析功能

clip icon clip

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

comad icon comad

official code for paper entitled "Component-aware anomaly detection framework for adjustable and logical industrial visual inspection"

cs-flow icon cs-flow

This is the official repository to the WACV 2022 paper "Fully Convolutional Cross-Scale-Flows for Image-based Defect Detection" by Marco Rudolph, Tom Wehrbein, Bodo Rosenhahn and Bastian Wandt.

cv icon cv

✔️最全面的 深度学习CV 笔记【吴恩达 深度学习】【李沐 动手学深度学习】【我是土堆 Pytorch】

davit icon davit

[ECCV 2022]Code for paper "DaViT: Dual Attention Vision Transformer"

deeplearning-500-questions icon deeplearning-500-questions

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

dinov2 icon dinov2

PyTorch code and models for the DINOv2 self-supervised learning method.

efficientad icon efficientad

Unofficial implementation of EfficientAD https://arxiv.org/abs/2303.14535

faiss icon faiss

A library for efficient similarity search and clustering of dense vectors.

freia icon freia

Framework for Easily Invertible Architectures

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