Trending repositories for topic few-shot-learning
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
A curated list of awesome prompt/adapter learning methods for vision-language models like CLIP.
This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc
A collection of AWESOME things about domian adaptation
This repository contains the implementation for the paper "Revisiting Few Shot Object Detection with Vision-Language Models"
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.
LibFewShot: A Comprehensive Library for Few-shot Learning. TPAMI 2023.
This repository contains the implementation for the paper "Revisiting Few Shot Object Detection with Vision-Language Models"
A curated list of awesome prompt/adapter learning methods for vision-language models like CLIP.
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.
LibFewShot: A Comprehensive Library for Few-shot Learning. TPAMI 2023.
This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc
A collection of AWESOME things about domian adaptation
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
A curated list of awesome prompt/adapter learning methods for vision-language models like CLIP.
This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc
A collection of AWESOME things about domian adaptation
Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
[pip install medmnist] 18x Standardized Datasets for 2D and 3D Biomedical Image Classification
This repository contains the implementation for the paper "Revisiting Few Shot Object Detection with Vision-Language Models"
Awesome papers about generative Information Extraction (IE) using Large Language Models (LLMs)
LibFewShot: A Comprehensive Library for Few-shot Learning. TPAMI 2023.
TensorFlow and PyTorch implementation of "Meta-Transfer Learning for Few-Shot Learning" (CVPR2019)
Implementations of few-shot object detection benchmarks
LLMs can generate feedback on their work, use it to improve the output, and repeat this process iteratively.
Official implementation of the paper 'Exploring Robust Features for Few-Shot Object Detection in Satellite Imagery'
CVPR 2023: Language in a Bottle: Language Model Guided Concept Bottlenecks for Interpretable Image Classification
(CVPR 2021) Few-Shot Classification with Feature Map Reconstruction Networks
pytorch implementation of Optimization as a Model for Few-shot Learning
This repository contains the implementation for the paper "Revisiting Few Shot Object Detection with Vision-Language Models"
Official implementation of the paper 'Exploring Robust Features for Few-Shot Object Detection in Satellite Imagery'
A curated list of awesome prompt/adapter learning methods for vision-language models like CLIP.
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
CVPR 2023: Language in a Bottle: Language Model Guided Concept Bottlenecks for Interpretable Image Classification
(CVPR 2021) Few-Shot Classification with Feature Map Reconstruction Networks
pytorch implementation of Optimization as a Model for Few-shot Learning
Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.
[pip install medmnist] 18x Standardized Datasets for 2D and 3D Biomedical Image Classification
Awesome papers about generative Information Extraction (IE) using Large Language Models (LLMs)
LibFewShot: A Comprehensive Library for Few-shot Learning. TPAMI 2023.
This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc
TensorFlow and PyTorch implementation of "Meta-Transfer Learning for Few-Shot Learning" (CVPR2019)
A collection of AWESOME things about domian adaptation
Implementations of few-shot object detection benchmarks
LLMs can generate feedback on their work, use it to improve the output, and repeat this process iteratively.
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
A curated list of awesome prompt/adapter learning methods for vision-language models like CLIP.
Awesome papers about generative Information Extraction (IE) using Large Language Models (LLMs)
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
A collection of AWESOME things about domian adaptation
Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.
[pip install medmnist] 18x Standardized Datasets for 2D and 3D Biomedical Image Classification
[WACV 2025] Official implementation of "RAW-Diffusion: RGB-Guided Diffusion Models for High-Fidelity RAW Image Generation"
LibFewShot: A Comprehensive Library for Few-shot Learning. TPAMI 2023.
Implementations of few-shot object detection benchmarks
LLMs can generate feedback on their work, use it to improve the output, and repeat this process iteratively.
This repository contains the implementation for the paper "Revisiting Few Shot Object Detection with Vision-Language Models"
Official implementation of CVPR 2024 PromptAD: Learning Prompts with Only Normal Samples for Few-Shot Anomaly Detection
TensorFlow and PyTorch implementation of "Meta-Transfer Learning for Few-Shot Learning" (CVPR2019)
[NeurIPS 2023] The Rise of AI Language Pathologists: Exploring Two-level Prompt Learning for Few-shot Weakly-supervised Whole Slide Image Classification
[WACV 2025] Official implementation of "RAW-Diffusion: RGB-Guided Diffusion Models for High-Fidelity RAW Image Generation"
This repository contains the implementation for the paper "Revisiting Few Shot Object Detection with Vision-Language Models"
[NeurIPS 2023] The Rise of AI Language Pathologists: Exploring Two-level Prompt Learning for Few-shot Weakly-supervised Whole Slide Image Classification
A curated list of awesome prompt/adapter learning methods for vision-language models like CLIP.
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
Official implementation of the paper 'Exploring Robust Features for Few-Shot Object Detection in Satellite Imagery'
Official implementation of CVPR 2024 PromptAD: Learning Prompts with Only Normal Samples for Few-Shot Anomaly Detection
Graph Information Aggregation Cross-domain Few-shot Learning for Hyperspectral Image Classification. IEEE TNNLS, 2022.
Awesome papers about generative Information Extraction (IE) using Large Language Models (LLMs)
The summary of code and paper for few-shot learning in fine-grained recognition
Source code for NeurIPS 2020 paper "Meta-Learning with Adaptive Hyperparameters"
CVPR 2023: Language in a Bottle: Language Model Guided Concept Bottlenecks for Interpretable Image Classification
Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.
[CVPR 2022] Official Pytorch Implementation for "Spatio-temporal Relation Modeling for Few-shot Action Recognition". SOTA Results for Few-shot Action Recognition
This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc
A curated list of awesome prompt/adapter learning methods for vision-language models like CLIP.
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
Official implementation of CVPR 2024 PromptAD: Learning Prompts with Only Normal Samples for Few-Shot Anomaly Detection
[ECCV 2024] - Improving Zero-shot Generalization of Learned Prompts via Unsupervised Knowledge Distillation
This repository contains the implementation for the paper "Revisiting Few Shot Object Detection with Vision-Language Models"
Service to import data from various sources and index it in AI Search. Increases data relevance and reduces final size by 90%+. Useful for RAG scenarios with LLM. Hosted in Azure with serverless archi...
[WACV 2025] Official implementation of "RAW-Diffusion: RGB-Guided Diffusion Models for High-Fidelity RAW Image Generation"
This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
Awesome papers about generative Information Extraction (IE) using Large Language Models (LLMs)
A curated list of awesome prompt/adapter learning methods for vision-language models like CLIP.
A collection of AWESOME things about domian adaptation
Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
LLMs can generate feedback on their work, use it to improve the output, and repeat this process iteratively.
[pip install medmnist] 18x Standardized Datasets for 2D and 3D Biomedical Image Classification
LibFewShot: A Comprehensive Library for Few-shot Learning. TPAMI 2023.
Official implementation of CVPR 2024 PromptAD: Learning Prompts with Only Normal Samples for Few-Shot Anomaly Detection
A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch
Implementations of few-shot object detection benchmarks
Learning to Learn using One-Shot Learning, MAML, Reptile, Meta-SGD and more with Tensorflow
X-Trend: Few-Shot Learning Patterns in Financial Time-Series for Trend-Following Strategies
Official Code for "SingularTrajectory: Universal Trajectory Predictor using Diffusion Model (CVPR 2024)"
[NeurIPS 2023] The Rise of AI Language Pathologists: Exploring Two-level Prompt Learning for Few-shot Weakly-supervised Whole Slide Image Classification
[WACV 2025] Official implementation of "RAW-Diffusion: RGB-Guided Diffusion Models for High-Fidelity RAW Image Generation"
[ECCV 2024] - Improving Zero-shot Generalization of Learned Prompts via Unsupervised Knowledge Distillation
Official repo for the TMLR paper "Discffusion: Discriminative Diffusion Models as Few-shot Vision and Language Learners"
Awesome papers about generative Information Extraction (IE) using Large Language Models (LLMs)
Evolve your OpenCV Image Processing filters using Cartesian Genetic Programming
A few shot learning repository for bearing fault diagnosis.
(CVPR2023) The PyTorch implementation of the "AsyFOD: An Asymmetric Adaptation Paradigm for Few-Shot Domain Adaptive Object Detection".
LLMs can generate feedback on their work, use it to improve the output, and repeat this process iteratively.
CVPR 2023: Language in a Bottle: Language Model Guided Concept Bottlenecks for Interpretable Image Classification
The summary of code and paper for few-shot learning in fine-grained recognition
FlexKBQA: A Flexible LLM-Powered Framework for Few-Shot Knowledge Base Question Answering
Few-shot Object Counting and Detection (ECCV 2022)
[ICLR2023] PLOT: Prompt Learning with Optimal Transport for Vision-Language Models
Implementation of our paper "Optimizing PatchCore for Few/many-shot Anomaly Detection"