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20182026
most citedAffective Computing for Large-Scale Heterogeneous Multimedia Data: A Survey

79 citations · 111 across the 9 of their papers we have counts for

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6 papers · 1 filter

cs.CV20232 cited

LibreFace: An Open-Source Toolkit for Deep Facial Expression Analysis

Di Chang, Yufeng Yin, Zongjian Li +2

Facial expression analysis is an important tool for human-computer interaction. In this paper, we introduce LibreFace, an open-source toolkit for facial expression analysis. This o…

cs.CV20231 cited

FG-Net: Facial Action Unit Detection with Generalizable Pyramidal Features

Yufeng Yin, Di Chang, Guoxian Song +5

Automatic detection of facial Action Units (AUs) allows for objective facial expression analysis. Due to the high cost of AU labeling and the limited size of existing benchmarks, p…

cs.CV20235 cited

Multi-modal Facial Action Unit Detection with Large Pre-trained Models for the 5th Competition on Affective Behavior Analysis in-the-wild

Yufeng Yin, Minh Tran, Di Chang +2

Facial action unit detection has emerged as an important task within facial expression analysis, aimed at detecting specific pre-defined, objective facial expressions, such as lip…

cs.CV2021

Modeling Dynamics of Facial Behavior for Mental Health Assessment

Minh Tran, Ellen Bradley, Michelle Matvey +2

Facial action unit (FAU) intensities are popular descriptors for the analysis of facial behavior. However, FAUs are sparsely represented when only a few are activated at a time. In…

cs.CV201922 cited

Polysemous Visual-Semantic Embedding for Cross-Modal Retrieval

Yale Song, Mohammad Soleymani

Visual-semantic embedding aims to find a shared latent space where related visual and textual instances are close to each other. Most current methods learn injective embedding func…

cs.CV2018

Cross-Modal Retrieval with Implicit Concept Association

Yale Song, Mohammad Soleymani

Traditional cross-modal retrieval assumes explicit association of concepts across modalities, where there is no ambiguity in how the concepts are linked to each other, e.g., when w…