[TPAMI 2023] Non-Graph Data Clustering via O(n) Bipartite Graph Convolution

L-Verse: Bidirectional Generation Between Image and Text

NÜWA-LIP: Language Guided Image Inpainting with Defect-free VQGAN

This is the official PyTorch implementation of the paper Open-Vocabulary Semantic Segmentation with Mask-adapted CLIP.

[CVPR 2023] Unofficial re-implementation of "WinCLIP: Zero-/Few-Shot Anomaly Classification and Segmentation".

Awesome-3D/Multimodal-Anomaly-Detection-and-Localization/Segmentation/3D-KD/3D-knowledge-distillation

[CVPR 2023] Pytorch Implementation for CVPR2023 paper: Explicit Boundary Guided Semi-Push-Pull Contrastive Learning for Supervised Anomaly Detection

Unofficial implementation of Google "CutPaste: Self-Supervised Learning for Anomaly Detection and Localization" in PyTorch

Papers for Video Anomaly Detection, released codes collection, Performance Comparision.

Contrastive Predictive Coding for Automatic Speaker Verification

Public repo for Augmented Multiscale Deep InfoMax representation learning

PyTorch implementation of Contrastive Learning methods

PyTorch implementation for COMPLETER: Incomplete Multi-view Clustering via Contrastive Prediction (CVPR 2021)

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

Official code for 'Deep One-Class Classification via Interpolated Gaussian Descriptor' [AAAI 2022 Oral]

Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors

This is an unofficial implementation of Reconstruction by inpainting for visual anomaly detection (RIAD).

Official Implementation for the "Back to the Feature: Classical 3D Features are (Almost) All You Need for 3D Anomaly Detection" paper (VAND Workshop - CVPR 2023).

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

Student–Teacher Anomaly Detection with Discriminative Latent Embeddings

A PyTorch implementation for exploring deep and shallow knowledge distillation (KD) experiments with flexibility

Code to reproduce 'MOCCA: Multi-Layer One-Class Classification for Anomaly Detection'

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

Improving Unsupervised Defect Segmentation by Applying Structural Similarity to Autoencoders

Anomaly detection in industrial dataset(MVTEC) like capsules, texture, bottle tec... with simple layers and high performance

Anomaly Detection via Reverse Distillation from One-Class Embedding