77 research outputs found
DARTS: Double Attention Reference-based Transformer for Super-resolution
We present DARTS, a transformer model for reference-based image
super-resolution. DARTS learns joint representations of two image distributions
to enhance the content of low-resolution input images through matching
correspondences learned from high-resolution reference images. Current
state-of-the-art techniques in reference-based image super-resolution are based
on a multi-network, multi-stage architecture. In this work, we adapt the double
attention block from the GAN literature, processing the two visual streams
separately and combining self-attention and cross-attention blocks through a
gating attention strategy. Our work demonstrates how the attention mechanism
can be adapted for the particular requirements of reference-based image
super-resolution, significantly simplifying the architecture and training
pipeline. We show that our transformer-based model performs competitively with
state-of-the-art models, while maintaining a simpler overall architecture and
training process. In particular, we obtain state-of-the-art on the SUN80
dataset, with a PSNR/SSIM of 29.83 / .809. These results show that attention
alone is sufficient for the RSR task, without multiple purpose-built
subnetworks, knowledge distillation, or multi-stage training
A finite element model of the face including an orthotropic skin model under in vivo tension
Computer models of the human face have the potential to be used as powerful tools in surgery simulation and animation development applications. While existing models accurately represent various anatomical features of the face, the representation of the skin and soft tissues is very simplified. A computer model of the face is proposed in which the skin is represented by an orthotropic hyperelastic constitutive model. The in vivo tension inherent in skin is also represented in the model. The model was tested by simulating several facial expressions by activating appropriate orofacial and jaw muscles.
Previous experiments calculated the change in orientation of the long axis of elliptical wounds on patients’ faces for wide opening of the mouth and an open-mouth smile (both 30 degrees). These results were compared with the average change of maximum principal stress direction in the skin calculated in the face model for wide opening of the mouth (18o) and an openmouth smile (25 degrees). The displacements of landmarks on the face for four facial expressions were compared with experimental
measurements in the literature. The corner of the mouth in the model experienced the largest displacement for each facial expression (11–14 mm). The simulated landmark displacements were within a standard deviation of the measured displacements. Increasing the skin stiffness and skin tension generally resulted in a reduction in landmark displacements upon facial expression
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