7,644 research outputs found
Depth Assisted Full Resolution Network for Single Image-based View Synthesis
Researches in novel viewpoint synthesis majorly focus on interpolation from
multi-view input images. In this paper, we focus on a more challenging and
ill-posed problem that is to synthesize novel viewpoints from one single input
image. To achieve this goal, we propose a novel deep learning-based technique.
We design a full resolution network that extracts local image features with the
same resolution of the input, which contributes to derive high resolution and
prevent blurry artifacts in the final synthesized images. We also involve a
pre-trained depth estimation network into our system, and thus 3D information
is able to be utilized to infer the flow field between the input and the target
image. Since the depth network is trained by depth order information between
arbitrary pairs of points in the scene, global image features are also involved
into our system. Finally, a synthesis layer is used to not only warp the
observed pixels to the desired positions but also hallucinate the missing
pixels with recorded pixels. Experiments show that our technique performs well
on images of various scenes, and outperforms the state-of-the-art techniques
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PDE Face: A Novel 3D Face Model
YesWe introduce a novel approach to face models, which
exploits the use of Partial Differential Equations (PDE) to
generate the 3D face. This addresses some common
problems of existing face models. The PDE face benefits
from seamless merging of surface patches by using only a
relatively small number of parameters based on boundary
curves. The PDE face also provides users with a great
degree of freedom to individualise the 3D face by
adjusting a set of facial boundary curves. Furthermore, we
introduce a uv-mesh texture mapping method. By
associating the texels of the texture map with the vertices
of the uv mesh in the PDE face, the new texture mapping
method eliminates the 3D-to-2D association routine in
texture mapping. Any specific PDE face can be textured
without the need for the facial expression in the texture
map to match exactly that of the 3D face model
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