arXiv:2607. 03581v1 Announce Type: cross Abstract: The widespread adoption of facial masks, accelerated by COVID-19 and mandated in security-sensitive settings, has exposed limitations of conventional face recognition systems.
arXiv:2601. 01406v2 Announce Type: replace-cross Abstract: Face super-resolution aims to recover high-quality facial images from severely degraded low-resolution inputs, but remains challenging due to the loss of fine structural details and identity-specific features.
arXiv:2608. 10346v1 Announce Type: cross Abstract: Although advancements in face landmark detection (FLD) methods continue to push performance boundaries, they overlook two major functional limitations: (1) different network parameters need to be trained independently for each ``$N$-point'' benchmark dataset, and (2) a model trained on an ``$N$-point'' dataset reliably outputs only the $N$ landmarks.
arXiv:2607. 03073v1 Announce Type: cross Abstract: Criminal identification from surveillance imagery has become a critical research area in intelligent forensic surveillance systems due to the increasing deployment of CCTV cameras in public and private environments.
Acne vulgaris affects most adolescents and many adults. Accurate severity grading guides treatment, monitoring, and clinical trial endpoints, but manual assessment using the Investigator's Global Assessment or Hayashi criteria is limited by inter-rater variability and inconsistent imaging conditions.
arXiv:2407. 13922v3 Announce Type: replace-cross Abstract: Face recognition (FR) systems are widely deployed in critical applications, making their reliability and robustness across diverse populations and conditions essential.
arXiv:2606. 15129v1 Announce Type: cross Abstract: Color fundus photography (CFP) is the mainstay for large-scale retinal screening, yet its diagnostic capacity is constrained by the lack of depth-resolved structural information.
arXiv:2607. 16273v1 Announce Type: cross Abstract: In forensic environments, automated identification of perpetrators is difficult due to pose changes, changes in light, occlusion, and lack of labeled data.
arXiv:2409. 00240v2 Announce Type: replace-cross Abstract: Automatic facial action unit (AU) recognition is used widely in facial expression analysis.
arXiv:2604. 07282v2 Announce Type: replace-cross Abstract: Automated face recognition has made rapid strides over the past decade due to the unprecedented rise of deep neural network (DNN) models that can be trained for domain-specific tasks.
arXiv:2607. 03959v1 Announce Type: cross Abstract: Diabetic retinopathy (DR) is a leading cause of vision impairment worldwide, highlighting the need for accurate and accessible screening tools.
arXiv:2608. 08521v1 Announce Type: cross Abstract: Face recognition systems face two distinct, commonly-separated failure modes: spoofing, where an impostor presents a photograph or video of an authorized user, and disguise, where a legitimate user is rejected because their appearance differs from their enrolled template due to accessories, facial hair, illumination, or pose.
arXiv:2606. 28628v1 Announce Type: cross Abstract: Localized generative editing needs localized evaluation: full-image identity metrics are structurally confounded under hard-composited edits.