Is Synthetic Data all We Need? Benchmarking the Robustness of Models
Trained with Synthetic Images

Is Synthetic Data all We Need? Benchmarking the Robustness of Models Trained with Synthetic Images

30 May 2024

Krishnakant Singh

Thanush Navaratnam

Jannik Holmer

Simone Schaub-Meyer

Papers citing "Is Synthetic Data all We Need? Benchmarking the Robustness of Models Trained with Synthetic Images"

6 / 6 papers shown

Title
Ctrl-GenAug: Controllable Generative Augmentation for Medical Sequence Classification Xinrui Zhou Yuhao Huang Haoran Dou Shijing Chen Ao Chang ... Jie Jessie Ren Ruobing Huang Jun Cheng Wufeng Xue Dong Ni MedIm 84 0 0 25 Sep 2024
SynthCLIP: Are We Ready for a Fully Synthetic CLIP Training? Hasan Hammoud Hani Itani Fabio Pizzati Philip H. S. Torr Adel Bibi Bernard Ghanem CLIP VLM 112 35 0 02 Feb 2024
BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models Junnan Li Dongxu Li Silvio Savarese Steven C. H. Hoi VLM MLLM 259 4,223 0 30 Jan 2023
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 258 7,412 0 11 Nov 2021
Emerging Properties in Self-Supervised Vision Transformers Mathilde Caron Hugo Touvron Ishan Misra Hervé Jégou Julien Mairal Piotr Bojanowski Armand Joulin 292 5,761 0 29 Apr 2021
Scaling Laws for Neural Language Models Jared Kaplan Sam McCandlish T. Henighan Tom B. Brown B. Chess R. Child Scott Gray Alec Radford Jeff Wu Dario Amodei 226 4,424 0 23 Jan 2020