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20182022
most citedExact Feature Distribution Matching for Arbitrary Style Transfer and Domain Generalization

16 citations · 24 across the 3 of their papers we have counts for

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cs.CV202216 cited

Exact Feature Distribution Matching for Arbitrary Style Transfer and Domain Generalization

Yabin Zhang, Minghan Li, Ruihuang Li +2

Arbitrary style transfer (AST) and domain generalization (DG) are important yet challenging visual learning tasks, which can be cast as a feature distribution matching problem. Wit…

cs.CV2022

One-stage Video Instance Segmentation: From Frame-in Frame-out to Clip-in Clip-out

Minghan Li, Lei Zhang

Many video instance segmentation (VIS) methods partition a video sequence into individual frames to detect and segment objects frame by frame. However, such a frame-in frame-out (F…

cs.CV20218 cited

Spatial Feature Calibration and Temporal Fusion for Effective One-stage Video Instance Segmentation

Minghan Li, Shuai Li, Lida Li +1

Modern one-stage video instance segmentation networks suffer from two limitations. First, convolutional features are neither aligned with anchor boxes nor with ground-truth boundin…

cs.CV2020

Learning to Rank for Active Learning: A Listwise Approach

Minghan Li, Xialei Liu, Joost van de Weijer +1

Active learning emerged as an alternative to alleviate the effort to label huge amount of data for data hungry applications (such as image/video indexing and retrieval, autonomous…

cs.CV2019

Video Rain/Snow Removal by Transformed Online Multiscale Convolutional Sparse Coding

Minghan Li, Xiangyong Cao, Qian Zhao +3

Video rain/snow removal from surveillance videos is an important task in the computer vision community since rain/snow existed in videos can severely degenerate the performance of…