TiP-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling

Last update: Jan 04, 2023

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Overview

TiP-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling

This is the official code release for the paper 'TiP-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling'.

Introduction

Tip-Adapter provides faster convergence and better performance than CLIP-Adapter by initializing the adapter with a cache model.

Implementation

Put tip_adapter_ImageNet.py into clip's folder and run

python tip_adapter_ImageNet.py

you will get 65.51% on ImageNet validation set.

This repo will be completed in a few days.

Contributors

Peng Gao, Renrui Zhang

Acknowledgment

CLIP, CoOp and CLIP-Adapter

Owner

peng gao

Young Scientist at Shanghai AI Lab

GitHub Repository

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TiP-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling

Related tags

Overview

TiP-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling

Introduction

Implementation

Contributors

Acknowledgment

Owner

peng gao

Implementation of Convolutional enhanced image Transformer

NBEATSx: Neural basis expansion analysis with exogenous variables

The authors' implementation of Unsupervised Adversarial Learning of 3D Human Pose from 2D Joint Locations

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Dual Attention Network for Scene Segmentation (CVPR2019)

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Anagram Generator in Python

Implementation of Multistream Transformers in Pytorch

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3D HourGlass Networks for Human Pose Estimation Through Videos

This code is an implementation for Singing TTS.

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