16,235 research outputs found
Visual Communications on the Road in Arkansas: Analysis of Secondary Students Videos
In the summer of 2010, the Visual Communications on the Road in Arkansas: Creative Photo and Video Projects to Promote Agriculture program was initiated. The program consisted of a two-week agricultural communications curriculum that would be taught by agricultural science teachers in Arkansas. The curriculum was composed of lessons about photography, writing, and videography, and the program introduced students to digital photography and videography equipment and the proper uses of equipment. Once the curriculum was taught in secondary schools, a mobile classroom unit—consisting of a travel trailer, photography and videography equipment, and laptop computers equipped with editing software—would visit the school to assist students with the creation of short promotional videos about agriculture. The student-created videos were used as a hands-on extension of the curriculum learned in the classroom. Completed videos were posted to YouTube and then analyzed to assess student application of competencies taught in the curriculum. The researchers created a coding sheet to systematically assess all posted videos and inter- and intrarater reliability was maintained. An analysis of data gathered from the video assessment showed that secondary students were able to effectively apply many of the techniques taught in the curriculum through the agricultural videos created. Additional findings and recommendations for application and future research are presented
Geometry-Aware Face Completion and Editing
Face completion is a challenging generation task because it requires
generating visually pleasing new pixels that are semantically consistent with
the unmasked face region. This paper proposes a geometry-aware Face Completion
and Editing NETwork (FCENet) by systematically studying facial geometry from
the unmasked region. Firstly, a facial geometry estimator is learned to
estimate facial landmark heatmaps and parsing maps from the unmasked face
image. Then, an encoder-decoder structure generator serves to complete a face
image and disentangle its mask areas conditioned on both the masked face image
and the estimated facial geometry images. Besides, since low-rank property
exists in manually labeled masks, a low-rank regularization term is imposed on
the disentangled masks, enforcing our completion network to manage occlusion
area with various shape and size. Furthermore, our network can generate diverse
results from the same masked input by modifying estimated facial geometry,
which provides a flexible mean to edit the completed face appearance. Extensive
experimental results qualitatively and quantitatively demonstrate that our
network is able to generate visually pleasing face completion results and edit
face attributes as well
Extreme 3D Face Reconstruction: Seeing Through Occlusions
Existing single view, 3D face reconstruction methods can produce beautifully
detailed 3D results, but typically only for near frontal, unobstructed
viewpoints. We describe a system designed to provide detailed 3D
reconstructions of faces viewed under extreme conditions, out of plane
rotations, and occlusions. Motivated by the concept of bump mapping, we propose
a layered approach which decouples estimation of a global shape from its
mid-level details (e.g., wrinkles). We estimate a coarse 3D face shape which
acts as a foundation and then separately layer this foundation with details
represented by a bump map. We show how a deep convolutional encoder-decoder can
be used to estimate such bump maps. We further show how this approach naturally
extends to generate plausible details for occluded facial regions. We test our
approach and its components extensively, quantitatively demonstrating the
invariance of our estimated facial details. We further provide numerous
qualitative examples showing that our method produces detailed 3D face shapes
in viewing conditions where existing state of the art often break down.Comment: Accepted to CVPR'18. Previously titled: "Extreme 3D Face
Reconstruction: Looking Past Occlusions
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