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Is facial beauty in the eyes? A multi-method approach to interpreting facial beauty prediction in machine learning models

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Discover Artificial Intelligence 2025年第1期5卷 1-18页

作者： Ibrahim, Ahmed Aman Ugail, Noah Hassan Ugail, Hassan Centre for Visual Computing and Intelligent Systems University of Bradford Bradford United Kingdom Department of Mathematical Sciences University of Bath Bath United Kingdom

Despite advances in facial beauty prediction, how specific facial regions contribute to perceptions of attractiveness remains largely unexplored, highlighting a critical interpretability gap in this domain. This study addresses the interpretability gap in facial beauty prediction (FBP) models by introducing a novel framework that combines global and local interpretability methods. We introduce Region Attribution, a technique that aggregates XRAI (eXplanation with Ranked Area Integrals) saliency maps across predefined facial regions to quantify their relative importance in individual predictions. Two global approaches complement this local interpretability: permutation feature importance, which systematically explores individual facial regions across the dataset to measure performance degradation, and individual feature prediction, where separate CNN models are trained on isolated facial regions to assess their independent predictive power. Using the SCUT-FBP5500 and MEBeauty datasets, we train convolutional neural networks on both full faces and individual facial features. While our findings reveal slight variations in feature rankings across the three methods, they consistently identify the eyes and nose regions as crucial determinants in facial beauty prediction. Thus, this study demonstrates the value of a multi-method approach in understanding the complex interplay of facial features in beauty prediction machine learning models. © The Author(s) 2025.

关键词： Prediction models

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An integrated framework for developing and evaluating a lecture style assessment methodology

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Multimedia Tools and Applications 2024年 1-28页

作者： Dimitriadou, Eleni Lanitis, Andreas Visual Media Computing Lab Department of Multimedia and Graphic Arts Cyprus University of Technology Limassol Cyprus CYENS Centre of Excellence Nicosia Cyprus

The aim of the work presented in this paper is to develop and evaluate an integrated lecture style evaluation methodology that provides, teachers instant feedback related to the quality of their lecturing style. The proposed method aims to promote improvement of lecture quality, that could upgrade the overall student learning experience. The proposed methodology utilizes specific measurable visual, and audio biometric characteristics extracted from a video showing the lecturer from the audience’s point of view. Measurable biometric features extracted during a lecture are combined to provide teachers with a score reflecting lecture style quality both at frame rate and by providing lecture quality metrics for the whole lecture. The results of a comprehensive quantitative evaluation indicate that the proposed methodology can be used for obtaining metrics that reflect lecture style quality. Furthermore, the performance evaluation of the proposed methodology was compared with the performance of humans in the task of lecture style evaluation. Results indicate that the proposed method not only achieves similar performance to human observers, but in some cases, it outperforms them. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Biometrics

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Puppetry in Tangible Narratives: Interactive and Collaborative Storytelling in The Non-myth of the Noble Red 24

Puppetry in Tangible Narratives: Interactive and Collaborati...

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18th International Conference on Tangible, Embedded, and Embodied Interaction, TEI 2024

作者： Echeverri, Daniel Atelier of Graphic Design and Multimedia Department of Visual Computing Faculty of Informatics Masaryk University Czech Republic

ISBN: (纸本)9798400704024

The Non-myth of the Noble Red is a tangible narrative that combines cardboard puppets with digital storytelling in an integrated physical storyworld. This narrative employs networked microcontrollers within the puppets, RFID readers, and sensors to enable interactivity. The narrative unfolds within three physical, interactive environments. Each environment can track the puppets' positions and trigger audio fragments of the story. Performers use these puppets to navigate the narrative, interact with objects, and engage in a battle. This project explores the potential of puppets as virtual and physical avatars, emphasising interactive and collaborative storytelling. It seeks to look at the impact of these puppets and the potential emerging social dynamics during the narrative experience. The work presented here contributes to tangible narratives by emphasising an integrated physical storyworld (instead of a mapped one) and utilising puppets as storytelling artefacts that serve as both input devices and virtual/physical avatars, promoting immersive and collaborative storytelling. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Interactive Storytelling Puppetry Tangible Interaction Tangible Narrative

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An approach in Applying Software Quality Assurance in Academic application: Case study of Student Information System - International Student Module (ISM)

An approach in Applying Software Quality Assurance in Academ...

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2023 International Conference on Mathematical and Statistical Physics, Computational Science, Education and Communication, ICMSCE 2023

作者： Suradi, Nur Razia Mohd Shukor, Nur Syufiza Ahmad Nar, Nik Nordiana Adnan, Zuraidy Hassan, Wan Azlan Wan Abdullah, Khairul Annuar Amil, Mohd Azril Selangor University Computing Department Faculty Communication Visual Art and Computing Malaysia Selangor University Faculty of Engineering and Life Sciences Malaysia

ISBN: (纸本)9781510671768

Software Quality Assurance (SQA) is a way to verify quality in the software. It is the set of activities which make certain processes, procedures as well as standards fit for the project and implemented appropriately. SQA is a process which works parallel to the development of software. It concentrates on improving the software development process so problems can be avoided. SQA is an activity that is applied throughout the software process, which will bring value to the project by saving money and time, implementing stable, competitive, and safe product, building constant process, helping to meet client expectations, and will create good developer’s reputation among the users. SQA can give significant impact to the software project in an academic environment with high defect removal efficiency which decreases the cost of software development and satisfy the users and target customers with respective to their expectations. Based on the implementation of SQA in International Student Module (ISM), the result showed that the error could be minimized beside reduced time effort in developing the software. © 2023 SPIE.

关键词： Acceptance tests

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NEURAL IMPLICIT SHAPE EDITING USING BOUNDARY SENSITIVITY 11

NEURAL IMPLICIT SHAPE EDITING USING BOUNDARY SENSITIVITY

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11th International Conference on Learning Representations, ICLR 2023

作者： Berzins, Arturs Ibing, Moritz Kobbelt, Leif Department of Mathematics and Cybernetics SINTEF Norway Visual Computing Institute RWTH Aachen University Germany

Neural fields are receiving increased attention as a geometric representation due to their ability to compactly store detailed and smooth shapes and easily undergo topological changes. Compared to classic geometry representations, however, neural representations do not allow the user to exert intuitive control over the shape. Motivated by this, we leverage boundary sensitivity to express how perturbations in parameters move the shape boundary. This allows to interpret the effect of each learnable parameter and study achievable deformations. With this, we perform geometric editing: finding a parameter update that best approximates a globally prescribed deformation. Prescribing the deformation only locally allows the rest of the shape to change according to some prior, such as semantics or deformation rigidity. Our method is agnostic to the model its training and updates the NN in-place. Furthermore, we show how boundary sensitivity helps to optimize and constrain objectives (such as surface area and volume), which are difficult to compute without first converting to another representation, such as a mesh. © 2023 11th International Conference on Learning Representations, ICLR 2023. All rights reserved.

关键词： Semantics

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Interpreting Equivariant Representations 41

Interpreting Equivariant Representations

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41st International Conference on Machine Learning, ICML 2024

作者： Hansen, Andreas Abildtrup Calissano, Anna Feragen, Aasa Department of Visual Computing Technical University of Denmark Kgs. Lyngby Denmark INRIA Université Côte d'Azur France

Latent representations are extensively used for tasks like visualization, interpolation, or feature extraction in deep learning models. This paper demonstrates the importance of considering the inductive bias imposed by an equivariant model when using latent representations as neglecting these biases can lead to decreased performance in downstream tasks. We propose principles for choosing invariant projections of latent representations and show their effectiveness in two examples: A permutation equivariant variational autoencoder for molecular graph generation, where an invariant projection can be designed to maintain information without loss, and for a rotation-equivariant representation in image classification, where random invariant projections proves to retain a high degree of information. In both cases, the analysis of invariant latent representations proves superior to their equivariant counterparts. Finally, we illustrate that the phenomena documented here for equivariant neural networks have counterparts in standard neural networks where invariance is encouraged via augmentation. Copyright 2024 by the author(s)

关键词： Image classification

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POTENTIAL AND CHALLENGES OF ASSURANCE CASES FOR SIMULATION VALIDATION

POTENTIAL AND CHALLENGES OF ASSURANCE CASES FOR SIMULATION V...

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2024 Winter Simulation Conference, WSC 2024

作者： Wilsdorf, Pia Zschaler, Steffen Haack, Fiete Uhrmacher, Adelinde M. Institute for Visual and Analytic Computing University of Rostock Rostock Germany Department of Informatics King’s College London London United Kingdom

ISBN: (纸本)9798331534202

Simulation studies require thorough validation to ensure model accuracy, reliability, and credibility. While validation typically focuses on the simulation model itself, additional artifacts also influence study outcomes. Conceptual models, comprising research questions, requirements, inputs and outputs, model content, assumptions, and simplifications, provide context information for interpreting results and assessing model suitability. Validating other simulation artifacts for their fitness-for-purpose is complex, necessitating structured arguments to increase confidence. This paper explores when and how validation arguments should be constructed throughout the modeling and simulation lifecycle. Drawing on concepts from safety assurance cases, it defines key claims for the various artifacts, discusses validation arguments from different perspectives – including process, product, people, and project – and illustrates them through a computational biology case study. We conclude with a discussion of the suitability of such structured arguments for the comprehensive validation of simulation studies. © 2024 IEEE.

关键词： Digital elevation model

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Contemporary visual computing: A system perspective

Contemporary visual computing: A system perspective

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2022 IEEE Region 10 International Conference, TENCON 2022

作者： Chen, Chang-Wen Chair Professor of Visual Computing Department of Computing The Hong Kong Polytechnic University Hong Kong

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Deep panoramic depth prediction and completion for indoor scenes

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Computational visual Media 2024年第5期10卷 903-922页

作者： Giovanni Pintore Eva Almansa Armando Sanchez Giorgio Vassena Enrico Gobbetti Visual and Data-intensive Computing CRS4Cagliari 09134Italy Gexcel srl Elmas(CA)09097Italy Department of Civil EnvironmentArchitectural Engineeringand Mathematics(DICATAM)Universita degli Studi di Brescia(UNIBS)Brescia(BS)25123Italy.

We introduce a novel end-to-end deeplearning solution for rapidly estimating a dense spherical depth map of an indoor *** input is a single equirectangular image registered with a sparse depth map,as provided by a variety of common capture *** is inferred by an efficient and lightweight single-branch network,which employs a dynamic gating system to process together dense visual data and sparse geometric *** exploit the characteristics of typical man-made environments to efficiently compress multiresolution features and find short-and long-range relations among scene ***,we introduce a new augmentation strategy to make the model robust to different types of sparsity,including those generated by various structured light sensors and LiDAR *** experimental results demonstrate that our method provides interactive performance and outperforms stateof-the-art solutions in computational efficiency,adaptivity to variable depth sparsity patterns,and prediction accuracy for challenging indoor data,even when trained solely on synthetic data without any fine tuning.

关键词： machine learning image processing and computervision visionand scene understanding 3D stereo scene analysis

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CLIP-Flow:Decoding images encoded in CLIP space

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Computational visual Media 2024年第6期10卷 1157-1168页

作者： Hao Ma Ming Li Jingyuan Yang Or Patashnik Dani Lischinski Daniel Cohen-Or Hui Huang Visual Computing Research Center College of Computer Science and Software EngineeringShenzhen UniversityShenzhen 518060China Department of Computer Science Tel Aviv UniversityTel Aviv 6997801Israel School of Computer Science and Engineering the Hebrew University of JerusalemJerusalem 91904Israel

This study introduces CLIP-Flow,a novel network for generating images from a given image or *** effectively utilize the rich semantics contained in both modalities,we designed a semantics-guided methodology for image-and text-to-image *** particular,we adopted Contrastive Language-Image Pretraining(CLIP)as an encoder to extract semantics and StyleGAN as a decoder to generate images from such ***,to bridge the embedding space of CLIP and latent space of StyleGAN,real NVP is employed and modified with activation normalization and invertible *** the images and text in CLIP share the same representation space,text prompts can be fed directly into CLIP-Flow to achieve text-to-image *** conducted extensive experiments on several datasets to validate the effectiveness of the proposed image-to-image synthesis *** addition,we tested on the public dataset Multi-Modal CelebA-HQ,for text-to-image *** validated that our approach can generate high-quality text-matching images,and is comparable with state-of-the-art methods,both qualitatively and quantitatively.

关键词： image-to-image text-to-image contrastive language-image pretraining(CLIP) flow StyleGAN

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