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View article: SketchPatch
SketchPatch Open
The paradigm of image-to-image translation is leveraged for the benefit of sketch stylization via transfer of geometric textural details. Lacking the necessary volumes of data for standard training of translation systems, we advocate for o…
View article: SketchPatch
SketchPatch Open
The paradigm of image-to-image translation is leveraged for the benefit of sketch stylization via transfer of geometric textural details. Lacking the necessary volumes of data for standard training of translation systems, we advocate for o…
View article: Neural Alignment for Face De-pixelization
Neural Alignment for Face De-pixelization Open
We present a simple method to reconstruct a high-resolution video from a face-video, where the identity of a person is obscured by pixelization. This concealment method is popular because the viewer can still perceive a human face figure a…
View article: Focus-and-Expand: Training Guidance Through Gradual Manipulation of Input Features
Focus-and-Expand: Training Guidance Through Gradual Manipulation of Input Features Open
We present a simple and intuitive Focus-and-eXpand (\fax) method to guide the training process of a neural network towards a specific solution. Optimizing a neural network is a highly non-convex problem. Typically, the space of solutions i…
View article: Image Morphing With Perceptual Constraints and STN Alignment
Image Morphing With Perceptual Constraints and STN Alignment Open
In image morphing, a sequence of plausible frames are synthesized and composited together to form a smooth transformation between given instances. Intermediates must remain faithful to the input, stand on their own as members of the set an…
View article: MeshCNN
MeshCNN Open
Polygonal meshes provide an efficient representation for 3D shapes. They explicitly captureboth shape surface and topology, and leverage non-uniformity to represent large flat regions as well as sharp, intricate features. This non-uniformi…
View article: ALIGNet: Partial-Shape Agnostic Alignment via Unsupervised Learning
ALIGNet: Partial-Shape Agnostic Alignment via Unsupervised Learning Open
The process of aligning a pair of shapes is a fundamental operation in computer graphics. Traditional approaches rely heavily on matching corresponding points or features to guide the alignment, a paradigm that falters when significant sha…
View article: Large-Scale 3D Shape Retrieval from ShapeNet Core55
Large-Scale 3D Shape Retrieval from ShapeNet Core55 Open
With the advent of commodity 3D capturing devices and better 3D modeling tools, 3D shape content is becoming increasingly prevalent. Therefore, the need for shape retrieval algorithms to handle large-scale shape repositories is more and mo…