2 citations · 4 across the 7 of their papers we have counts for
7 papers
BLM-Guard: Explainable Multimodal Ad Moderation with Chain-of-Thought and Policy-Aligned Rewards
Yiran Yang, Zhaowei Liu, Yuan Yuan +10
Short-video platforms now host vast multimodal ads whose deceptive visuals, speech and subtitles demand finer-grained, policy-driven moderation than community safety filters. We pr…
Predicting Scores of Various Aesthetic Attribute Sets by Learning from Overall Score Labels
Heng Huang, Xin Jin, Yaqi Liu +5
Now many mobile phones embed deep-learning models for evaluation or guidance on photography. These models cannot provide detailed results like human pose scores or scene color scor…
An Order-Complexity Model for Aesthetic Quality Assessment of Symbolic Homophony Music Scores
Xin Jin, Wu Zhou, Jinyu Wang +3
Computational aesthetics evaluation has made great achievements in the field of visual arts, but the research work on music still needs to be explored. Although the existing work o…
Aesthetic Visual Question Answering of Photographs
Xin Jin, Wu Zhou, Xinghui Zhou +4
Aesthetic assessment of images can be categorized into two main forms: numerical assessment and language assessment. Aesthetics caption of photographs is the only task of aesthetic…
Aesthetic Attributes Assessment of Images with AMANv2 and DPC-CaptionsV2
Xinghui Zhou, Xin Jin, Jianwen Lv +3
Image aesthetic quality assessment is popular during the last decade. Besides numerical assessment, nature language assessment (aesthetic captioning) has been proposed to describe…
Aesthetic Attribute Assessment of Images Numerically on Mixed Multi-attribute Datasets
Xin Jin, Xinning Li, Hao Lou +5
With the continuous development of social software and multimedia technology, images have become a kind of important carrier for spreading information and socializing. How to evalu…
Pseudo-labelling and Meta Reweighting Learning for Image Aesthetic Quality Assessment
Xin Jin, Hao Lou, Huang Heng +4
In the tasks of image aesthetic quality evaluation, it is difficult to reach both the high score area and low score area due to the normal distribution of aesthetic datasets. To re…