liutongkun's repositories
memae-anomaly-detection
MemAE for anomaly detection. -- Gong, Dong, et al. "Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detection". ICCV 2019.
3d_url_survey
(TPAMI2023) Unsupervised Point Cloud Representation Learning with Deep Neural Networks: A Survey
AnomalyGPT
The first LVLM based IAD method!
awesome-industrial-anomaly-detection
Paper list and datasets for industrial image anomaly detection (defect detection). 工业异常检测(瑕疵检测)论文及数据集检索库。
ChatPaper
Use ChatGPT to summarize the arXiv papers. 全流程加速科研,利用chatgpt进行论文总结+润色+审稿+审稿回复
CVPR2023-Papers-with-Code
CVPR 2023 论文和开源项目合集
EfficientAD
Unofficial implementation of EfficientAD https://arxiv.org/abs/2303.14535
HFC
Implementation for the paper (CVPR Oral): High Frequency Component Helps Explain the Generalization of Convolutional Neural Networks
mixed-segdec-net-comind2021
Official PyTorch implementation for "Mixed supervision for surface-defect detection: from weakly to fully supervised learning"
MNAD
An official implementation of "Learning Memory-guided Normality for Anomaly Detection" (CVPR 2020) in PyTorch.
Point-MAE
[ECCV2022] Masked Autoencoders for Point Cloud Self-supervised Learning
pytorch-grad-cam
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
Shape-Guided
Shape-Guided Dual-Memory Learning for 3D Anomaly Detection [ICML2023]
Surface-Defect-Detection
📈 目前最大的工业缺陷检测数据库及论文集 Constantly summarizing open source dataset and critical papers in the field of surface defect research which are of great importance.
VAND-APRIL-GAN
CVPR 2023 Workshop VAND Challenge: 1st Place on Zero-shot AD and 4th Place on Few-shot AD