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.

The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use th…

[ICCV 2019] Monocular depth estimation from a single image

EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything

Self-study on Larry Wasserman's "All of Statistics"

A dataset of datasets for learning to learn from few examples

pytorch version of spatial transformer networks

[NeurIPS 2021] [T-PAMI] Global Filter Networks for Image Classification

TPAMI：Frequency-aware Feature Fusion for Dense Image Prediction

[IEEE-TMI'22] Causality-inspired Single-source Domain Generalization for Medical Image Segmentation (code&data-processing pipeline)

[AAAI 2023] Official PyTorch implementation of the paper "SLAug: Rethinking Data Augmentation for Single-source Domain Generalization in Medical Image Segmentation"

[AAAI 25] FAMNet: Frequency-aware Matching Network for Cross-domain Few-shot Medical Image Segmentation

[CVPR2024] Learning CNN on ViT: A Hybrid Model to Explicitly Class-specific Boundaries for Domain Adaptation