Could Giant Pretrained Image Models Extract Universal Representations?

3 November 2022

Papers citing "Could Giant Pretrained Image Models Extract Universal Representations?"

9 / 9 papers shown

Title
Enhancing Your Trained DETRs with Box Refinement Yiqun Chen Qiang Chen Pei Sun Shoufa Chen Jingdong Wang Jian Cheng 22 2 0 21 Jul 2023
RoMa: Robust Dense Feature Matching Johan Edstedt Qiyu Sun Georg Bökman Maarten Wadenback M. Felsberg 3DV 23 91 0 24 May 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
CPT: Colorful Prompt Tuning for Pre-trained Vision-Language Models Yuan Yao Ao Zhang Zhengyan Zhang Zhiyuan Liu Tat-Seng Chua Maosong Sun MLLM VPVLM VLM 194 220 0 24 Sep 2021
Learning to Prompt for Vision-Language Models Kaiyang Zhou Jingkang Yang Chen Change Loy Ziwei Liu VPVLM CLIP VLM 322 2,249 0 02 Sep 2021
The Power of Scale for Parameter-Efficient Prompt Tuning Brian Lester Rami Al-Rfou Noah Constant VPVLM 280 3,835 0 18 Apr 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 3,683 0 11 Feb 2021
Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation Golnaz Ghiasi Yin Cui A. Srinivas Rui Qian Tsung-Yi Lin E. D. Cubuk Quoc V. Le Barret Zoph ISeg 223 962 0 13 Dec 2020
Semantic Understanding of Scenes through the ADE20K Dataset Bolei Zhou Hang Zhao Xavier Puig Tete Xiao Sanja Fidler Adela Barriuso Antonio Torralba SSeg 249 1,821 0 18 Aug 2016