Less is More: Removing Text-regions Improves CLIP Training Efficiency
and Robustness

Less is More: Removing Text-regions Improves CLIP Training Efficiency and Robustness

8 May 2023

Chen Chen

Xianzhi Du

Wen‐Cheng Zhang

Papers citing "Less is More: Removing Text-regions Improves CLIP Training Efficiency and Robustness"

5 / 5 papers shown

Title
Efficient Self-Supervised Learning for Earth Observation via Dynamic Dataset Curation Thomas Kerdreux A. Tuel Quentin Febvre A. Mouche Bertrand Chapron 73 0 0 09 Apr 2025
PreSTU: Pre-Training for Scene-Text Understanding Jihyung Kil Soravit Changpinyo Xi Chen Hexiang Hu Sebastian Goodman Wei-Lun Chao Radu Soricut VLM 120 29 0 12 Sep 2022
TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models Minghao Li Tengchao Lv Jingye Chen Lei Cui Yijuan Lu D. Florêncio Cha Zhang Zhoujun Li Furu Wei ViT 87 214 0 21 Sep 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 273 845 0 17 Feb 2021
Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision Chao Jia Yinfei Yang Ye Xia Yi-Ting Chen Zarana Parekh Hieu H. Pham Quoc V. Le Yun-hsuan Sung Zhen Li Tom Duerig VLM CLIP 293 2,875 0 11 Feb 2021