activity
20172020
most citedDeep Multimodality Learning for UAV Video Aesthetic Quality Assessment

29 citations · 42 across the 6 of their papers we have counts for

collaborators

8 papers

cs.CV202029 cited

Deep Multimodality Learning for UAV Video Aesthetic Quality Assessment

Qi Kuang, Xin Jin, Qinping Zhao +1

Despite the growing number of unmanned aerial vehicles (UAVs) and aerial videos, there is a paucity of studies focusing on the aesthetics of aerial videos that can provide valuable…

cs.CV2020

A Deep Drift-Diffusion Model for Image Aesthetic Score Distribution Prediction

Xin Jin, Xiqiao Li, Heng Huang +2

The task of aesthetic quality assessment is complicated due to its subjectivity. In recent years, the target representation of image aesthetic quality has changed from a one-dimens…

cs.CV2019

Aesthetic Attributes Assessment of Images

Xin Jin, Le Wu, Geng Zhao +6

Image aesthetic quality assessment has been a relatively hot topic during the last decade. Most recently, comments type assessment (aesthetic captions) has been proposed to describ…

cs.CV20197 cited

Facial Makeup Transfer Combining Illumination Transfer

Xin Jin, Rui Han, Ning Ning +2

To meet the women appearance needs, we present a novel virtual experience approach of facial makeup transfer, developed into windows platform application software. The makeup effec…

cs.CV2017

Single Reference Image based Scene Relighting via Material Guided Filtering

Xin Jin, Yannan Li, Ningning Liu +4

Image relighting is to change the illumination of an image to a target illumination effect without known the original scene geometry, material information and illumination conditio…

cs.CV2017

Privacy Preserving Face Retrieval in the Cloud for Mobile Users

Xin Jin, Shiming Ge, Chenggen Song

Recently, cloud storage and processing have been widely adopted. Mobile users in one family or one team may automatically backup their photos to the same shared cloud storage space…