wenxixi

awesome-DeepLearning

深度学习入门课、资深课、特色课、学术案例、产业实践案例、深度学习知识百科及面试题库The course, case and knowledge of Deep Learning and AI

Data-Science-Interview-Questions-Answers

Curated list of data science interview questions and answers

CHOLEC80-CVS-PUBLIC

Endoscapes

Official Repository for the Endoscapes Dataset for Surgical Scene Segmentation, Object Detection, and Critical View of Safety Assessment

Awesome-Medical-Large-Language-Models

Curated papers on Large Language Models in Healthcare and Medical domain

Awesome-Remote-Sensing-Foundation-Models

bolei_awesome_posters

CVPR and NeurIPS poster examples and templates. May we have in-person poster session soon!

EfficientSAM

EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything

CLIP

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

USFM

Awesome-Healthcare-Foundation-Models

ISINet

Pytorch implementation of the MICCAI 2020 paper ISINet: An Instance-Based Approach for Surgical Instrument Segmentation.

TAPIR

peft

🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.

CoOp

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

vpt

❄️🔥 Visual Prompt Tuning [ECCV 2022] https://arxiv.org/abs/2203.12119

ViPT

[CVPR23] Visual Prompt Multi-Modal Tracking

AdaptFormer

[NeurIPS 2022] Implementation of "AdaptFormer: Adapting Vision Transformers for Scalable Visual Recognition"

Caption-Anything

Caption-Anything is a versatile tool combining image segmentation, visual captioning, and ChatGPT, generating tailored captions with diverse controls for user preferences. https://huggingface.co/spaces/TencentARC/Caption-Anything https://huggingface.co/spaces/VIPLab/Caption-Anything

SAMed

The implementation of the technical report: "Customized Segment Anything Model for Medical Image Segmentation"

SAM4MIS

SAM & SAM 2 for Medical Image Segmentation: Open-Source Project Summary

Personalize-SAM

Personalize Segment Anything Model (SAM) with 1 shot in 10 seconds

LoRA

Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"

Segment-Everything-Everywhere-All-At-Once

[NeurIPS 2023] Official implementation of the paper "Segment Everything Everywhere All at Once"

Painter

Painter & SegGPT Series: Vision Foundation Models from BAAI

SAM-Adapter-PyTorch

Adapting Meta AI's Segment Anything to Downstream Tasks with Adapters and Prompts

Medical-SAM-Adapter

Adapting Segment Anything Model for Medical Image Segmentation

Awesome-Anything

General AI methods for Anything: AnyObject, AnyGeneration, AnyModel, AnyTask, AnyX

Track-Anything

Track-Anything is a flexible and interactive tool for video object tracking and segmentation, based on Segment Anything, XMem, and E2FGVI.

Semantic-Segment-Anything

Automated dense category annotation engine that serves as the initial semantic labeling for the Segment Anything dataset (SA-1B).