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Found 10 papers, 3 papers with code
Self-supervised High-fidelity and Re-renderable 3D Facial Reconstruction from a Single Image
Although each method has its own advantage, none of them is capable of recovering a high-fidelity and re-renderable facial texture, where the term 're-renderable' demands the facial texture to be spatially complete and disentangled with environmental illumination.
Robust Multi-view Registration of Point Sets with Laplacian Mixture Model
The proposed method assumes each data point is generated by a Laplacian Mixture Model (LMM), where its centers are determined by the corresponding points in other point sets.
Compound eye inspired flat lensless imaging with spatially-coded Voronoi-Fresnel phase
We demonstrate and verify the imaging performance with a prototype Voronoi-Fresnel lensless camera on a 1. 6-megapixel image sensor in various illumination conditions.
Text-Aware Single Image Specular Highlight Removal
The core goal is to improve the accuracy of text detection and recognition by removing the highlight from text images.
LARNet: Lie Algebra Residual Network for Face Recognition
We prove that face rotation in the image space is equivalent to an additive residual component in the feature space of CNNs, which is determined solely by the rotation.
Scene text removal via cascaded text stroke detection and erasing
Specifically, we decouple the text removal problem into text stroke detection and stroke removal.
Pixel-wise Dense Detector for Image Inpainting
Recent GAN-based image inpainting approaches adopt an average strategy to discriminate the generated image and output a scalar, which inevitably lose the position information of visual artifacts.
MGCN: Descriptor Learning using Multiscale GCNs
Second, we propose a new multiscale graph convolutional network (MGCN) to transform a non-learned feature to a more discriminative descriptor.
Detecting Colorized Images via Convolutional Neural Networks: Toward High Accuracy and Good Generalization
First, we design and implement a base network, which can attain better performance in terms of classification accuracy and generalization (in most cases) compared with state-of-the-art methods.
Learning 3D Keypoint Descriptors for Non-Rigid Shape Matching
In this paper, we present a novel deep learning framework that derives discriminative local descriptors for 3D surface shapes.
