A nearly final program for our workshop here, July 25-6th is now available. The posters are still a bit fluid: if you’d like to bring one, please let me know.
In keeping with the workshop format, we’re allowing extended time for discussion after each set of talks
To book attendance, which is free: https://faceresearch.stir.ac.uk/july-workshop/
Peter
Program
Thursday 25th July
9:00 Registration
Session 1 Face representations
9:30 How the learning of unfamiliar faces is affected by their resemblance to familiar faces
Katie L.H. Gray, Maddie Atkinson, Kay Ritchie, Peter Hancock
9:50 How Does Increased Familiarity Change Face Representation in Memory?
Mintao Zhao, Isabelle Bülthoff
10:10 The contribution of distinctive features to cost-efficient facial representations
Christel Devue and Mathieu Blondel
10:30 Discussion
10:50 Coffee break
11:30 Keynote 1: Meike Ramon: Unique traits, computational insights: studying Super-Recognizers for societal applications
12:30 Lunch
Session 2: Decision making
13:30 Human computer teaming with low mismatch incidence,
Anna Bobak, Melina Muller, Peter Hancock
13:50 Unfamiliar face matching and metacognitive efficiency
Robin Kramer, Robert McIntosh
14:10 Distinct criterion placement for intermixed face matching tasks
Kristen A. Baker, Markus Bindemann
14:30 Discussion
14:50 Break and posters
16:00 Keynote 2: Alice O’Toole: Dissecting Face Representations in Deep Neural Networks: Implications for Rethinking Neural Codes
17:00 Break
18:00 Public Lecture: Peter Hancock: Face recognition by humans and computers: criminal injustice?
19: 30 Dinner
Friday 26th July
Session 3: Factors affecting face recognition
9:30 Face masks and fake masks: Have we been underestimating the problem of face masks in face identity perception?
Kay L Ritchie, Daniel J Carragher, Josh P Davis, Katie Read, Ryan E Jenkins, Eilidh Noyes, Katie LH Gray, Peter JB Hancock
9:50 Identification of masked faces: typical observers, super-recognisers, forensic examiners and algorithms.
Eilidh Noyes, Reuben Moreton, Peter Hancock, Kay Ritchie, Sergio Castro Martinez, Katie Gray, and Josh Davis
10:10 Individual variation, socio-emotional functioning and face perception
Karen Lander, Grace Talbot, Anastasia Murphy & Richard Brown
10:30 Discussion
10:50 Coffee
Session 4: Identification of suspects
11:20 Identity Recognition of Composites Constructed of Unfamiliar Faces
Charlie Frowd
11:40 Inverse caricature effects in eyewitness identification performance and deep learning models of face recognition
Gaia Giampietro, Ryan McKay, Thora Bjornsdottir, Laura Mickes, Nicholas Furl
12:00 Implicit markers of concealed face recognition
Ailsa Millen
12:20 Discussion
13:00 Workshop end
Posters
As good as it gets? Computer-enhanced recognition of single-view faces does not improve performance across matching or recognition tasks. Scott P Jones, Peter Hancock
"They're just not my cup of tea": random preferences are more important than random effects in modelling facial attractiveness ratings. Thomas Hancock, Peter Hancock, Anthony Lee, Morgan Sidari, Amy Zhao, Brendan Zietsch
Investigating the modulatory effects of emotional expressions on short-term face familiarity. Constantin-Iulian Chiță, Simon Paul Liversedge, Philipp Ruhnau
Human-computer teaming with low quality images. Dan Carragher, Peter Hancock, David White
Wisdom of the crowds, within and between individuals, Dan Carragher and Peter Hancock
Islands of Expertise and face matching. Emily Cunningham, Anna Bobak, Peter Hancock
Investigating Face Recognition Ability in Neurodiverse Individuals. Caelan Dow, Anna Bobak, Jud Lowes
The Heterogeneity of Face Processing in Developmental Prosopagnosia from a Single Case Analysis Approach, Benjamin Armstrong, Anna Bobak, Jud Lowes
The effects of age on face recognition. Zsofi Kovacs-Bodo, Stephen Langton, Peter Hancock & Anna Bobak
Seeing through the lies: effectiveness of eye-tracking measures for the detection of concealed recognition of newly familiar faces and objects. Amir Shapira and Ailsa Millen
Peter Hancock (he/him)
Professor
Psychology, School of Natural Sciences
University of Stirling
FK9 4LA, UK
phone 01786 467675
http://rms.stir.ac.uk/converis-stirling/person/11587
@pjbhancock
Latest papers:
Face masks and fake masks: the effect of real and superimposed masks on face matching with super-recognisers, typical observers, and algorithms https://rdcu.be/dxAIR
Balanced Integration Score: A new way of classifying Developmental Prosopagnosia
https://www.sciencedirect.com/science/article/abs/pii/S0010945224000054
My messages may arrive outside of the working day but this does not imply any expectation that you should reply outside of your normal working hours. If you wish to respond, please do so when convenient.
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________________________________
Scotland’s University for Sporting Excellence
The University of Stirling is a charity registered in Scotland, number SC 011159
We (Abhijit Das, Mayank Vatsa, Richa Singh, Arun Ross, Vitomir Štruc,
Antitza Dantcheva, Ph.D. and Raghavendra Ramachandra) are organising the
1st Computer Vision for Biometrics, Identity & Behaviour (CV4BIOM) workshop
at ICCV 2025.
Submission deadline: *1 July 2025 (23:59 AoE), no further extension*
Decision: 11 July 2025
Website: cv4biom.org
Submission link:
https://openreview.net/group?id=thecvf.com/ICCV/2025/Workshop/CV4BIOM
Submission guideline: ICCV Author Guidelines
<https://iccv.thecvf.com/Conferences/2025/AuthorGuidelines>
All accepted papers in the workshops will be published in the ICCV workshop
proceedings:
ICCVW will only include works longer than 4 pages and up to 8 pages, not
including references.
***********The best-reviewed paper from the workshop will be invited to
submit extended work to the IEEE TBIOM SPECIAL ISSUE on Best Reviewed
Papers from ICCV 2025 Biometrics.***************
Topics of interest, but not limited to:
• Biometrics & Identity: Technologies, Applications, and Challenges:
– Biometric Modalities and Sensors: Face, fingerprint, ear, eye (iris,
retina), vein pat-
terns, palm, gait, and emerging biometric traits.
– Biometric Processing and Computation: Template generation, feature
extraction,
matching algorithms, and dataset baselines.
– Multi-Biometrics and Fusion: Information fusion, normalization
techniques, machine
learning-based integration, and theoretical models.
– Privacy, Security and Bias: Bias mitigation, privacy-preserving
techniques, security
assessments, and adversarial robustness in biometric systems.
– Forensic and Law Enforcement Applications: Biometrics in forensics, crime
investi-
gation, and security assessment.
– Biometrics in Technology and Industry: Mobile and wearable devices,
banking, IoT,
large-scale identity management, and biometric authentication standards.
– Emerging Challenges and Ethical Considerations: Digital data forensics,
biometric
deepfakes, synthetic realities, ethical, social, and legal issues in
biometric adoption.
• Behavior Understanding & Applications:
– Multimodal Behavior Modeling: Human and animal behavior analysis, social
interac-
tions, empathy, and emotional intelligence.
– Generative and Machine Learning Approaches: Advanced learning models for
be-
havior prediction and synthesis.
– Sensor Technologies and Data Fusion: Multisensory solutions, information
fusion tech-
niques, and integration for behavior analysis.
– Datasets and Benchmarks: Standardized datasets and evaluation metrics for
behavior
recognition and prediction.
– Attention and Perception Analysis: Visual attention, visual saliency, and
cognitive
modeling.
– Assistive and Inclusive Technologies: Applications for the visually and
hearing im-
paired, sign language recognition, and assistive living solutions.
– Personalized and Health-Centric Applications: Monitoring for aging
populations,
child development, and quality-of-life technologies.
– Egocentric and First-Person Vision: Wearable vision-based applications
for personal-
ized assistance and behaviour tracking.
Best regards
Abhijit
------------------ --------------------- ---- --------------------
*Dr.** Abhijit Das, * PhD, SMIEEE, LMIUPRAI, Member APPCAIR
<https://appcair.com/applied-ai-faculty.html>
Lead Investigator, Machine Intelligence Group
<https://sites.google.com/hyderabad.bits-pilani.ac.in/mig/home>
Assistant Professor.
<https://sites.google.com/hyderabad.bits-pilani.ac.in/mig/home>
<https://sites.google.com/hyderabad.bits-pilani.ac.in/mig/home>
H112, Dept. of Computer Science and Information Systems,
BITS Pilani, Hyderabad Campus.
*Organising Chair:*
1st Workshop on Computer Vision for Biometrics, Identity and Behaviour
(CV4BIB 2025) at ICCV 2025.
ICRA'2025 Satellite event at BITS Hyderabad
*Competition Co-Chairs: *IEEE International Joint Conference on Biometrics
(IJCB 2026)
*Sponsorship** Co-Chairs: *6th Indian Symposium on Machine Learning (IndoML
2025)
*Contact no:* +914066303744 (O)
*Website: *https://sites.google.com/site/dasabhijit2048/home
*▄▄▄▄▄▄▄▄▄▄▄▄**▄▄▄▄▄▄▄▄▄▄▄▄▄**▄▄▄▄▄▄▄▄▄▄▄▄*
[image: Visit Hyderabad Campus]
Dear Colleagues,
Please find below the invitation to contribute to the 8th Workshop and Competition on Affective & Behavior Analysis in-the-wild (ABAW)<https://affective-behavior-analysis-in-the-wild.github.io/8th/> to be held in conjunction with the IEEE Computer Vision and Pattern Recognition Conference (CVPR), 2025.
(1): The Competition is split into the below six Challenges:
*
Valence-Arousal Estimation Challenge
*
Expression Recognition Challenge
*
Action Unit Detection Challenge
*
Compound Expression Recognition Challenge
*
Emotional Mimicry Intensity Estimation Challenge
*
Ambivalence/Hesitancy (AH) Recognition Challenge
The first 3 Challenges are based on an augmented version of the Aff-Wild2 database, which is an A/V in-the-wild database of 594 videos of 584 subjects of around 3M frames; it contains annotations in terms of valence-arousal, expressions and action units.
The 4th Challenge is based on C-EXPR-DB, which is an A/V in-the-wild database and in total consists of 400 videos of around 200K frames; each frame is annotated in terms of compound expressions.
The 5th Challenge is based on the Hume-Vidmimic2 dataset, which is a multimodal dataset of about 75 hours of video recordings of 2222 subjects; it contains continuous annotations for the intensity of 7 emotional experiences.
The last Challenge is based on the Behavioural Ambivalence/Hesitancy dataset, which is an A/V dataset of 630 videos of 5 hours duration of around 430K frames; it contains annotations in terms of presence and absence of ambivalence/hesitancy.
Participants are invited to participate in at least one of these Challenges.
There will be one winner per Challenge; the top-3 performing teams of each Challenge will have to contribute paper(s) describing their approach, methodology and results to our Workshop; the accepted papers will be part of the CVPR 2025 proceedings; all other teams are also encouraged to submit paper(s) describing their solutions and final results; the accepted papers will be part of the CVPR 2025 proceedings.
More information about the Competition can be found here<https://affective-behavior-analysis-in-the-wild.github.io/8th/#clients>.
Important Dates:
* Call for participation announced, team registration begins, data available:
22 January, 2025
* Final submission deadline:
12 March, 2025
* Winners Announcement:
17 March, 2025
* Final paper submission deadline:
21 March, 2025
* Review decisions sent to authors; Notification of acceptance:
3 April, 2025
* Camera ready version deadline:
7 April, 2025
Chairs:
Dimitrios Kollias, Queen Mary University of London, UK
Stefanos Zafeiriou, Imperial College London, UK
Irene Kotsia, Cogitat Ltd, UK
Panagiotis Tzirakis, Hume AI
Alan Cowen, Hume AI
Eric Granger, École de technologie supérieure, Canada
Marco Pedersoli, École de technologie supérieure, Canada
Simon Bacon, Concordia University, Canada
(2): The Workshop solicits contributions on cutting-edge advancements in analyzing, generating, modeling, and understanding human affect and behavior across multiple modalities, including facial expressions, body movements, gestures and speech. A special emphasis is placed on the integration of state-of-the-art systems designed for in-the-wild analysis, enabling research and applications in unconstrained environments. In parallel, this Workshop will solicit contributions towards building fair, explainable, trustworthy and privacy-aware models that perform well on all subgroups and improve in-the-wild generalisation.
Original high-quality contributions, in terms of databases, surveys, studies, foundation models, techniques and methodologies (either uni-modal or multi-modal; uni-task or multi-task ones) are solicited on -but are not limited to- the following topics:
i) facial expression (basic, compound or other) or micro-expression analysis
ii) facial action unit detection
iii) valence-arousal estimation
iv) physiological-based (e.g.,EEG, EDA) affect analysis
v) face recognition, detection or tracking
vi) body recognition, detection or tracking
vii) gesture recognition or detection
viii) pose estimation or tracking
ix) activity recognition or tracking
x) lip reading and voice understanding
xi) face and body characterization (e.g., behavioral understanding)
xii) characteristic analysis (e.g., gait, age, gender, ethnicity recognition)
xiii) group understanding via social cues (e.g., kinship, non-blood relationships, personality)
xiv) video, action and event understanding
xv) digital human modeling
xvi) characteristic analysis (e.g., gait, age, gender, ethnicity recognition)
xvii) violence detection
xviii) autonomous driving
xix) domain adaptation, domain generalisation, few- or zero-shot learning for the above cases
xx) fairness, explainability, interpretability, trustworthiness, privacy-awareness, bias mitigation and/or subgroup distribution shift analysis for the above cases
xxi) editing, manipulation, image-to-image translation, style mixing, interpolation, inversion and semantic diffusion for all afore mentioned cases
Accepted workshop papers will appear at CVPR 2025 proceedings.
Important Dates:
Paper Submission Deadline: 21 March, 2025
Review decisions sent to authors; Notification of acceptance: 3 April, 2025
Camera ready version 7 April, 2025
Chairs:
Dimitrios Kollias, Queen Mary University of London, UK
Stefanos Zafeiriou, Imperial College London, UK
Irene Kotsia, Cogitat Ltd, UK
Panagiotis Tzirakis, Hume AI
Alan Cowen, Hume AI
Eric Granger, École de technologie supérieure, Canada
Marco Pedersoli, École de technologie supérieure, Canada
Simon Bacon, Concordia University, Canada
In case of any queries, please contact d.kollias(a)qmul.ac.uk<mailto:d.kollias@qmul.ac.uk>
Kind Regards,
Dimitrios Kollias,
on behalf of the organising committee
========================================================================
Dr Dimitrios Kollias, PhD, FHEA, M-IEEE, M-BMVA, M-AAAI, M-TCPAMI, AM-IAPR
Lecturer (Assistant Professor) in Artificial Intelligence
Member of Centre for Multimodal AI
Affiliate Member of Centre for Human Centred Computing
Member of Multimedia and Vision Group
Member of Queen Mary Computer Vision Group
Associate Member of Centre for Advanced Robotics
Academic Fellow of Digital Environment Research Institute
School of EECS
Queen Mary University of London
========================================================================