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Prompt Learning

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/farinamatteo/rethinking_fewshot_vlms

Low-Rank Few-Shot Adaptation of Vision-Language Models

https://github.com/farinamatteo/zero

Learning to Prompt for Vision-Language Models

https://github.com/gyukai/i2vc

MaPLe: Multi-modal Prompt Learning

https://github.com/haiv-lab/ospcoop_imagenet-bg

LoCoOp: Few-Shot Out-of-Distribution Detection via Prompt Learning

https://github.com/hanoonaR/object-centric-ovd

PromptDet: Towards Open-vocabulary Detection using Uncurated Images

https://github.com/htyao89/kgcoop

MaPLe: Multi-modal Prompt Learning

https://github.com/jia-hao999/samba

VSCode: General Visual Salient and Camouflaged Object Detection with 2D Prompt Learning

https://github.com/kaiyangzhou/on-device-dg

Learning to Prompt for Vision-Language Models

https://github.com/kenomo/industrial-clip

Learning to Prompt for Vision-Language Models

https://github.com/linxin0/scpgabnet

Re-boosting Self-Collaboration Parallel Prompt GAN for Unsupervised Image Restoration

https://github.com/lupantech/promptpg

Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoning

https://github.com/maxzanella/clip-lora

Low-Rank Few-Shot Adaptation of Vision-Language Models

https://github.com/mlvlab/dapt

Learning to Prompt for Vision-Language Models

https://github.com/muzairkhattak/protext

Learning to Prompt for Vision-Language Models

https://github.com/nirvanalan/ln3diff

MVDream: Multi-view Diffusion for 3D Generation

https://github.com/open3da/ll3da

MotionGPT: Human Motion as a Foreign Language

https://github.com/opendilab/DI-engine

Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoning

https://github.com/openmeshlab/meshxl

MotionGPT: Human Motion as a Foreign Language

https://github.com/schowdhury671/APoLLo

APoLLo: Unified Adapter and Prompt Learning for Vision Language Models

https://github.com/siyuanyan1/epvt

Prompt-driven Latent Domain Generalization for Medical Image Classification

https://github.com/srvcodes/clap4clip

Learning to Prompt for Vision-Language Models

https://github.com/super-buster/OpenPrompt

OpenPrompt: An Open-source Framework for Prompt-learning

https://github.com/xiangtaokong/tgbd

Towards Effective Multiple-in-One Image Restoration: A Sequential and Prompt Learning Strategy

https://github.com/yaphabates/restore_

RESTORE: Towards Feature Shift for Vision-Language Prompt Learning

https://github.com/ybzh/openood-vlm

LAPT: Label-driven Automated Prompt Tuning for OOD Detection with Vision-Language Models

https://github.com/zhipeixu/fakeshield

V2A-Mark: Versatile Deep Visual-Audio Watermarking for Manipulation Localization and Copyright Protection

https://github.com/zqhang/Accurate-WinCLIP-pytorch

AnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly Detection

https://github.com/zqhang/WinCLIP-pytorch

AnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly Detection

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.