DreamDA: Generative Data Augmentation with Diffusion Models

DreamDA: Generative Data Augmentation with Diffusion Models

19 March 2024

Yunxiang Fu

Chaoqi Chen

Papers citing "DreamDA: Generative Data Augmentation with Diffusion Models"

7 / 7 papers shown

Title
D-Feat Occlusions: Diffusion Features for Robustness to Partial Visual Occlusions in Object Recognition Rupayan Mallick Sibo Dong Nataniel Ruiz Sarah Adel Bargal DiffM 42 0 0 08 Apr 2025
Muse: Text-To-Image Generation via Masked Generative Transformers Huiwen Chang Han Zhang Jarred Barber AJ Maschinot José Lezama ... Kevin Patrick Murphy William T. Freeman Michael Rubinstein Yuanzhen Li Dilip Krishnan DiffM 197 515 0 02 Jan 2023
Diffusion Models: A Comprehensive Survey of Methods and Applications Ling Yang Zhilong Zhang Yingxia Shao Shenda Hong Runsheng Xu Yue Zhao Wentao Zhang Bin Cui Ming-Hsuan Yang DiffM MedIm 213 1,277 0 02 Sep 2022
Zero-Shot Text-to-Image Generation Aditya A. Ramesh Mikhail Pavlov Gabriel Goh Scott Gray Chelsea Voss Alec Radford Mark Chen Ilya Sutskever VLM 253 4,735 0 24 Feb 2021
Aggregated Residual Transformations for Deep Neural Networks Saining Xie Ross B. Girshick Piotr Dollár Z. Tu Kaiming He 261 10,106 0 16 Nov 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 247 9,042 0 06 Jun 2015
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 279 39,083 0 01 Sep 2014