# PersEmoN: A Deep Network for Joint Analysis of Apparent Personality, Emotion and Their Relationship

arXiv: https://arxiv.org/abs/1811.08657 · HTML: https://mlsanity.com/paper/1811.08657/

## Key facts

- Cited by 15 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Nov 2018.

## Built on by (most cited first, 15 of 15)

- [A Survey on Personality-Aware Recommendation Systems](https://mlsanity.com/paper/2101.12153/) (2021)
- [SVFAP: Self-supervised Video Facial Affect Perceiver](https://mlsanity.com/paper/2401.00416/) (2023)
- [Orders Are Unwanted: Dynamic Deep Graph Convolutional Network for Personality Detection](https://mlsanity.com/paper/2212.01515/) (2022)
- [Psycholinguistic Tripartite Graph Network for Personality Detection](https://mlsanity.com/paper/2106.04963/) (2021)
- [An Open-source Benchmark of Deep Learning Models for Audio-visual Apparent and Self-reported Personality Recognition](https://mlsanity.com/paper/2210.09138/) (2022)
- [MDPE: A Multimodal Deception Dataset with Personality and Emotional Characteristics](https://mlsanity.com/paper/2407.12274/) (2024)
- [Personality-Driven Social Multimedia Content Recommendation](https://mlsanity.com/paper/2207.12236/) (2022)
- [Learning Graph Representation of Person-specific Cognitive Processes from Audio-visual Behaviours for Automatic Personality Recognition](https://mlsanity.com/paper/2110.13570/) (2021)
- [Pose as a Modality: A Psychology-Inspired Network for Personality Recognition with a New Multimodal Dataset](https://mlsanity.com/paper/2503.12912/) (2025)
- [Domain-specific Learning of Multi-scale Facial Dynamics for Apparent Personality Traits Prediction](https://mlsanity.com/paper/2209.04148/) (2022)
- [PSA-MF: Personality-Sentiment Aligned Multi-Level Fusion for Multimodal Sentiment Analysis](https://mlsanity.com/paper/2512.01442/) (2025)
- [Learning Person-specific Network Representation for Apparent Personality Traits Recognition](https://mlsanity.com/paper/2303.01236/) (2023)
- [Automated Deception Detection from Videos: Using End-to-End Learning Based High-Level Features and Classification Approaches](https://mlsanity.com/paper/2307.06625/) (2023)
- [Enhancing Apparent Personality Trait Analysis with Cross-Modal Embeddings](https://mlsanity.com/paper/2405.03846/) (2024)
- [Multi-modal expressive personality recognition in data non-ideal audiovisual based on multi-scale feature enhancement and modal augment](https://mlsanity.com/paper/2503.06108/) (2025)

## Abstract (arXiv)

Apparent personality and emotion analysis are both central to affective computing. Existing works solve them individually. In this paper we investigate if such high-level affect traits and their relationship can be jointly learned from face images in the wild. To this end, we introduce PersEmoN, an end-to-end trainable and deep Siamese-like network. It consists of two convolutional network branches, one for emotion and the other for apparent personality. Both networks share their bottom feature extraction module and are optimized within a multi-task learning framework. Emotion and personality networks are dedicated to their own annotated dataset. Furthermore, an adversarial-like loss function is employed to promote representation coherence among heterogeneous dataset sources. Based on this, we also explore the emotion-to-apparent-personality relationship. Extensive experiments demonstrate the effectiveness of PersEmoN.