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Found 6 papers, 0 papers with code
Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing
Extrapolating fine-grained pixel-level correspondences in a fully unsupervised manner from a large set of misaligned images can benefit several computer vision and graphics problems, e. g. co-segmentation, super-resolution, image edit propagation, structure-from-motion, and 3D reconstruction.
DeSTNet: Densely Fused Spatial Transformer Networks
In this paper, we propose Densely Fused Spatial Transformer Network (DeSTNet), which, to our best knowledge, is the first dense fusion pattern for combining multiple STNs.
Robust Joint and Individual Variance Explained
Even though the CCA is a powerful tool, it has several drawbacks that render its application challenging for computer vision applications.
Robust Statistical Face Frontalization
The proposed method is assessed in frontal face reconstruction, face landmark localization, pose-invariant face recognition, and face verification in unconstrained conditions.
Face frontalization for Alignment and Recognition
The proposed method is assessed in frontal face reconstruction (pose correction), face landmark localization, and pose-invariant face recognition and verification by conducting experiments on $6$ facial images databases.
RAPS: Robust and Efficient Automatic Construction of Person-Specific Deformable Models
Next, to correct the fittings of a generic model, image congealing (i. e., batch image aliment) is performed by employing only the learnt orthonormal subspace.
