2020年6月17日 · When we train GPT‑2 on images unrolled into long sequences of pixels, which we call iGPT, we find that the model appears to understand 2-D image characteristics such as …

作者直接利用GPT-2 的模型结构，忽略图像的二维结构信息，直接将图像转化为一维序列作为输入，通过这这种方式地无监督生成式训练，GPT-2 在图像上也能学到很好的表达，预训练得到 …

Transformer家族的模型基本上可以直接处理任何形式的1D数据，于是研究人员就想到 将2D图像拉伸为长长的1D图像序列，利用与 GPT-2 模型类似的技术构建了用于处理像素序列的iGPT模型 …

This repository is meant to be a starting point for researchers and engineers to experiment with image GPT (iGPT). Our code forks GPT-2 to highlight that it can be easily applied across …

PyTorch implementation of Image GPT, based on paper Generative Pretraining from Pixels (Chen et al.) and accompanying code. Model-generated completions of half-images from test set. …

一个自然的图像到图像转换方法是学习给定输入的输出图像的条件分布，使用能够捕捉图像高维空间中的多模态分布的深度生成模型。 生成对抗网络（GANs）【Goodfellow等人2014; …

This paper enhances image-GPT (iGPT), one of the pioneering works that introduce autoregres-sive pretraining to predict the next pixels for vi-sual representation learning.

FastGPT 官方文档，提供详细的功能介绍、使用指南和开发者资源。

GPT-NEW Image Matching Using Global Projection Transformation Correlation and the Acceleration Algorithm Using Integral Images

2025年3月21日 · Objective: We will develop a deeper understanding of the structure and function of Frequent Small Group Purposeful Talk and, Closing Objective: I will discuss how I can apply …