Exploring Vision Transformers as Diffusion Learners

28 December 2022

Papers citing "Exploring Vision Transformers as Diffusion Learners"

7 / 7 papers shown

Title
How to Protect Copyright Data in Optimization of Large Language Models? T. Chu Zhao-quan Song Chiwun Yang 28 29 0 23 Aug 2023
Masked Diffusion Models Are Fast Distribution Learners Jiachen Lei Qinglong Wang Pengyu Cheng Zhongjie Ba Zhan Qin Zhibo Wang Zhenguang Liu Kui Ren DiffM 17 2 0 20 Jun 2023
DAB-DETR: Dynamic Anchor Boxes are Better Queries for DETR Shilong Liu Feng Li Hao Zhang X. Yang Xianbiao Qi Hang Su Jun Zhu Lei Zhang ViT 138 703 0 28 Jan 2022
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 258 7,337 0 11 Nov 2021
Palette: Image-to-Image Diffusion Models Chitwan Saharia William Chan Huiwen Chang Chris A. Lee Jonathan Ho Tim Salimans David J. Fleet Mohammad Norouzi DiffM VLM 325 1,570 0 10 Nov 2021
Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions Wenhai Wang Enze Xie Xiang Li Deng-Ping Fan Kaitao Song Ding Liang Tong Lu Ping Luo Ling Shao ViT 263 3,538 0 24 Feb 2021
Conceptual 12M: Pushing Web-Scale Image-Text Pre-Training To Recognize Long-Tail Visual Concepts Soravit Changpinyo P. Sharma Nan Ding Radu Soricut VLM 273 1,077 0 17 Feb 2021