Bi-modal First Impressions Recognition using Temporally Ordered Deep Audio and Stochastic Visual Features
We propose a novel approach for First Impressions Recognition in terms of the Big Five personality-traits from short videos. The Big Five personality traits is a model to describe human personality using five broad categories: Extraversion, Agreeableness, Conscientiousness, Neuroticism and Openness. We train two bi-modal end-to-end deep neural network architectures using temporally ordered audio and novel stochastic visual features from few frames, without over-fitting. We empirically show that the trained models perform exceptionally well, even after training from a small sub-portions of inputs. Our method is evaluated in ChaLearn LAP 2016 Apparent Personality Analysis (APA) competition using ChaLearn LAP APA2016 dataset and achieved excellent performance.
Code (1)
Similar Papers 제목 키워드 기반
Deep Impression: Audiovisual Deep Residual Networks for Multimodal Apparent Personality Trait Recognition
Here, we develop an audiovisual deep residual network for multimodal apparent personality trait recognition. The network is trained end-to-end for predicting the Big Five personality traits of people from their videos. T…
Facial Expression RecognitionFeature EngineeringPersonality Trait RecognitionCr-net: A deep classification-regression network for multimodal apparent personality analysis
First impressions strongly influence social interactions, having a high impact in the personal and professional life. In this paper, we present a deep Classification-Regression Network (CR-Net) for analyzing the Big Five…
Personality Trait Recognition by FaceregressionImpression-CLIP: Contrastive Shape-Impression Embedding for Fonts
Fonts convey different impressions to readers. These impressions often come from the font shapes. However, the correlation between fonts and their impression is weak and unstable because impressions are subjective. To ca…
Cross-Modal RetrievalRetrievalMulti-Scale Local-Temporal Similarity Fusion for Continuous Sign Language Recognition
Continuous sign language recognition (cSLR) is a public significant task that transcribes a sign language video into an ordered gloss sequence. It is important to capture the fine-grained gloss-level details, since there…
Sign Language RecognitionDeep set conditioned latent representations for action recognition
In recent years multi-label, multi-class video action recognition has gained significant popularity. While reasoning over temporally connected atomic actions is mundane for intelligent species, standard artificial neural…
Action RecognitionAtomic action recognitionComposite action recognitionTemporal Action Localization