317 research outputs found
Text-guided Eyeglasses Manipulation with Spatial Constraints
Virtual try-on of eyeglasses involves placing eyeglasses of different shapes
and styles onto a face image without physically trying them on. While existing
methods have shown impressive results, the variety of eyeglasses styles is
limited and the interactions are not always intuitive or efficient. To address
these limitations, we propose a Text-guided Eyeglasses Manipulation method that
allows for control of the eyeglasses shape and style based on a binary mask and
text, respectively. Specifically, we introduce a mask encoder to extract mask
conditions and a modulation module that enables simultaneous injection of text
and mask conditions. This design allows for fine-grained control of the
eyeglasses' appearance based on both textual descriptions and spatial
constraints. Our approach includes a disentangled mapper and a decoupling
strategy that preserves irrelevant areas, resulting in better local editing. We
employ a two-stage training scheme to handle the different convergence speeds
of the various modality conditions, successfully controlling both the shape and
style of eyeglasses. Extensive comparison experiments and ablation analyses
demonstrate the effectiveness of our approach in achieving diverse eyeglasses
styles while preserving irrelevant areas.Comment: Revised version: add some experiment
Infrared face recognition: a comprehensive review of methodologies and databases
Automatic face recognition is an area with immense practical potential which
includes a wide range of commercial and law enforcement applications. Hence it
is unsurprising that it continues to be one of the most active research areas
of computer vision. Even after over three decades of intense research, the
state-of-the-art in face recognition continues to improve, benefitting from
advances in a range of different research fields such as image processing,
pattern recognition, computer graphics, and physiology. Systems based on
visible spectrum images, the most researched face recognition modality, have
reached a significant level of maturity with some practical success. However,
they continue to face challenges in the presence of illumination, pose and
expression changes, as well as facial disguises, all of which can significantly
decrease recognition accuracy. Amongst various approaches which have been
proposed in an attempt to overcome these limitations, the use of infrared (IR)
imaging has emerged as a particularly promising research direction. This paper
presents a comprehensive and timely review of the literature on this subject.
Our key contributions are: (i) a summary of the inherent properties of infrared
imaging which makes this modality promising in the context of face recognition,
(ii) a systematic review of the most influential approaches, with a focus on
emerging common trends as well as key differences between alternative
methodologies, (iii) a description of the main databases of infrared facial
images available to the researcher, and lastly (iv) a discussion of the most
promising avenues for future research.Comment: Pattern Recognition, 2014. arXiv admin note: substantial text overlap
with arXiv:1306.160
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