Linhao-Qu

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.

CLIP

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

CoOp

Prompt Learning for Vision-Language Models (IJCV'22, CVPR'22)

Dassl.pytorch

A PyTorch toolbox for domain generalization, domain adaptation and semi-supervised learning.

DeepOD

Deep learning-based outlier/anomaly detection

openslide

C library for reading virtual slide images

WSAD

A Collection of Resources for Weakly-supervised Anomaly Detection (WSAD)

TransMEF

Official PyTorch implementation of our AAAI22 paper: TransMEF: A Transformer-Based Multi-Exposure Image Fusion Framework via Self-Supervised Multi-Task Learning.

patchmix

The official implementation of paper: "Inter-Instance Similarity Modeling for Contrastive Learning"

UR-DMU

Official code for AAAI2023 paper "Dual Memory Units with Uncertainty Regulation for Weakly Supervised Video Anomaly Detection"

MambaMIL

[MICCAI 2024] Official Code for "MambaMIL: Enhancing Long Sequence Modeling with Sequence Reordering in Computational Pathology"

WENO

Official PyTorch implementation of our NeurIPS 2022 paper: Weakly Supervised Knowledge Distillation for Whole Slide Image Classification

DGMIL

Official PyTorch implementation of our MICCAI 2022 paper: DGMIL: Distribution Guided Multiple Instance Learning for Whole Slide Image Classification.

MultiModal-learning

CU-Net

[CVPR 2023] Official code for paper: Exploiting Completeness and Uncertainty of Pseudo Labels for Weakly Supervised Video Anomaly Detection

FCMEF

This is a PyTorch/GPU implementation of the Information Fusion 2022 paper: Rethinking multi-exposure image fusion with extreme and diverse exposure levels: A robust framework based on Fourier transform and contrastive learning.:

LNMNet

Official Pytorch Implementation of our new paper 'Predicting Lymph Node Metastasis from Primary Cervical Cancer Based on Deep Learning in Histopathological Images.'