Cross-resolution Face Recognition via Identity-Preserving Network and Knowledge Distillation
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A large part of computer vision research is devoted to building models
and algorithms aimed at understanding human appearance and behaviour
from images and videos. Ultimately, we want to build automated systems
that are at least as capable as people when i ...
Visual scene recognition deals with the problem of automatically recognizing the high-level semantic concept describing a given image as a whole, such as the environment in which the scene is occurring (e.g. a mountain), or the event that is taking place ( ...
École Polytechnique Fédérale de Lausanne (EPFL)2014
Visual scene recognition deals with the problem of automatically recognizing the high-level semantic concept describing a given image as a whole, such as the environment in which the scene is occurring (e.g. a mountain), or the event that is taking place ( ...
Recent advances have shown the great power of deep convolutional neural networks (CNN) to learn the relationship between low and high-resolution image patches. However, these methods only take a single-scale image as input and require large amount of data ...
Super-resolving a natural image is an ill-posed problem. The classical approach is based on the registration and subsequent interpolation of a given set of low-resolution images. However, achieving satisfactory results typically requires the combination of ...
Estimating the 3D poses of rigid and articulated bodies is one of the fundamental problems of Computer Vision. It has a broad range of applications including augmented reality, surveillance, animation and human-computer interaction. Despite the ever-growin ...
Depth information is used in a variety of 3D based signal processing applications such as autonomous navigation of robots and driving systems, object detection and tracking, computer games, 3D television, and free view-point synthesis. These applications r ...
We consider the problem of super-resolution from unregistered aliased images with unknown spatial scaling factors and shifts. Due to the limitation of pixel size in the image sensor, the sampling rate for each image is lower than the Nyquist rate of the sc ...
Super-resolution reconstruction is a method for reconstructing higher resolution images from a set of low resolution observations. The sub-pixel differences among different observations of the same scene allow to create higher resolution images with better ...
We propose a robust and accurate method to extract the centerlines and scale of tubular structures in 2D images and 3D volumes. Existing techniques rely either on filters designed to respond to ideal cylindrical structures, which lose accuracy when the lin ...