activity
20192023
most citedMultimodal Contrastive Training for Visual Representation Learning

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

collaborators
Showing cs.CVShow all

12 papers · 1 filter

cs.CV2023★ 7 cited

Photoswap: Personalized Subject Swapping in Images

Jing Gu, Yilin Wang, Nanxuan Zhao +8

In an era where images and visual content dominate our digital landscape, the ability to manipulate and personalize these images has become a necessity. Envision seamlessly substit…

cs.CV2022★ 7 cited

Interactive Portrait Harmonization

Jeya Maria Jose Valanarasu, He Zhang, Jianming Zhang +7

Current image harmonization methods consider the entire background as the guidance for harmonization. However, this may limit the capability for user to choose any specific object/…

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…

cs.CV2020★ 4 cited

Meticulous Object Segmentation

Chenglin Yang, Yilin Wang, Jianming Zhang +3

Compared with common image segmentation tasks targeted at low-resolution images, higher resolution detailed image segmentation receives much less attention. In this paper, we propo…

cs.CV2020★ 4 cited

Mask Guided Matting via Progressive Refinement Network

Qihang Yu, Jianming Zhang, He Zhang +5

We propose Mask Guided (MG) Matting, a robust matting framework that takes a general coarse mask as guidance. MG Matting leverages a network (PRN) design which encourages the matti…

cs.CV2020★ 7 cited

An Overview Of 3D Object Detection

Yilin Wang, Jiayi Ye

Point cloud 3D object detection has recently received major attention and becomes an active research topic in 3D computer vision community. However, recognizing 3D objects in LiDAR…

cs.CV2020★ 1 cited

Incorporating Reinforced Adversarial Learning in Autoregressive Image Generation

Kenan E. Ak, Ning Xu, Zhe Lin +1

Autoregressive models recently achieved comparable results versus state-of-the-art Generative Adversarial Networks (GANs) with the help of Vector Quantized Variational AutoEncoders…

cs.CV2019★ 9 cited

Multimodal Style Transfer via Graph Cuts

Yulun Zhang, Chen Fang, Yilin Wang +4

An assumption widely used in recent neural style transfer methods is that image styles can be described by global statics of deep features like Gram or covariance matrices. Alterna…