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20192023
most citedMultimodal Contrastive Training for Visual Representation Learning

17 citations · 61 across the 13 of their papers we have counts for

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Showing 2021Show all

5 papers · 1 filter

cs.CV2021★ 2 cited

Lite Vision Transformer with Enhanced Self-Attention

Chenglin Yang, Yilin Wang, Jianming Zhang +4

Despite the impressive representation capacity of vision transformer models, current light-weight vision transformer models still suffer from inconsistent and incorrect dense predi…

cs.CV2021

SSH: A Self-Supervised Framework for Image Harmonization

Yifan Jiang, He Zhang, Jianming Zhang +7

Image harmonization aims to improve the quality of image compositing by matching the "appearance" (\eg, color tone, brightness and contrast) between foreground and background image…

cs.CV2021

Making CNNs Interpretable by Building Dynamic Sequential Decision Forests with Top-down Hierarchy Learning

Yilin Wang, Shaozuo Yu, Xiaokang Yang +1

In this paper, we propose a generic model transfer scheme to make Convlutional Neural Networks (CNNs) interpretable, while maintaining their high classification accuracy. We achiev…

cs.CV2021★ 17 cited

Multimodal Contrastive Training for Visual Representation Learning

Xin Yuan, Zhe Lin, Jason Kuen +5

We develop an approach to learning visual representations that embraces multimodal data, driven by a combination of intra- and inter-modal similarity preservation objectives. Unlik…

cs.CV2021

Classifying Video based on Automatic Content Detection Overview

Yilin Wang, Jiayi Ye

Video classification and analysis is always a popular and challenging field in computer vision. It is more than just simple image classification due to the correlation with respect…