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