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anomalyclip

Official implementation for AnomalyCLIP (ICLR 2024)

anomalydiffusion

[AAAI 2024] AnomalyDiffusion: Few-Shot Anomaly Image Generation with Diffusion Model

anomalygpt

[AAAI 2024 Oral] AnomalyGPT: Detecting Industrial Anomalies Using Large Vision-Language Models

dcfs

Decoupling Classifier for Boosting Few-shot Object Detection and Instance Segmentation (NeurIPS 2022)

draem

ds2

ds2deb

ds2 code for submission

efficientad

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

fapis

fct

fedsage

Code for Subgraph Federated Learning with Missing Neighbor Generation (NeurIPS 2021)

frustrating

Implementations of few-shot object detection benchmarks

fsod

FewX is an open-source toolbox on top of Detectron2 for data-limited instance-level recognition tasks.

fsod-code

ifs_rcnn

Official code for CVPR 2022 paper: "iFS-RCNN: An Incremental Few-shot Instance Segmenter"

ifsl

[CVPR'22] Official PyTorch implementation of Integrative Few-Shot Learning for Classification and Segmentation

imtfa

Code accompanying the paper 'Incremental Few-Shot Instance Segmentation'

loco_ad_eval

mae

PyTorch implementation of MAE https//arxiv.org/abs/2111.06377

musc

This is an official PyTorch implementation for "MuSc : Zero-Shot Industrial Anomaly Classification and Segmentation with Mutual Scoring of the Unlabeled Images" (MuSc ICLR2024).

patchcore

recontrast

segment-anything

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.

vand_april

[CVPR 2023 Workshop] VAND Challenge: 1st Place on Zero-shot AD and 4th Place on Few-shot AD