Abstract: An information processing method comprises: acquiring an original webpage; parsing the original webpage to determine a set of candidate images; detecting whether at least one candidate image in the set of candidate images contains a face; determining a target face from at least one detected face, and determining a candidate image corresponding to the target face as a target image; analyzing the target face to obtain at least one content feature of the original webpage, wherein the at least one content feature includes at least one of a face attribute feature and a personal identity feature; determining display contents matching the at least one content feature based on the at least one content feature; inserting the display contents into a target area corresponding to the target image in the original webpage in a form of a dialog box to acquire a target webpage; and outputting the target webpage.

Abstract: A picture management method and device, a picture synchronization method and device are disclosed. The picture management method can be applied to a client device, and comprises: receiving picture tags generated by a server device performing an image analysis based on original picture features received by the server device, the original picture feature being an original picture itself or original picture parameter(s); and classifying and archiving the original pictures represented by the original picture features according to the picture tags.

Abstract: An information processing method comprises: acquiring an original webpage; parsing the original webpage to determine a set of candidate images; detecting whether at least one candidate image in the set of candidate images contains a face; determining a target face from at least one detected face, and determining a candidate image corresponding to the target face as a target image; analyzing the target face to obtain at least one content feature of the original webpage, wherein the at least one content feature includes at least one of a face attribute feature and a personal identity feature; determining display contents matching the at least one content feature based on the at least one content feature; inserting the display contents into a target area corresponding to the target image in the original webpage in a form of a dialog box to acquire a target webpage; and outputting the target webpage.

Abstract: An information processing method and an information processing apparatus are provided, the method comprising: acquiring an original web page; resolving the original web page to determine a target image; analyzing at least one of the target image and context associated with the target image, to obtain a content feature of the original web page; determining display content matched with the content feature based on the content feature; inserting the display content into a target region corresponding to the target image, of the original web page, to obtain a target web page; and outputting the target web page.

Abstract: A picture management method and device, a picture synchronization method and device are disclosed. The picture management method can be applied to a client device, and comprises: receiving picture tags generated by a server device performing an image analysis based on original picture features received by the server device, the original picture feature being an original picture itself or original picture parameter(s); and classifying and archiving the original pictures represented by the original picture features according to the picture tags.

Abstract: A deep learning framework jointly optimizes the compactness and discriminative ability of face representations. The compact representation can be as compact as 32 bits and still produce highly discriminative performance. In another aspect, based on the extreme compactness, traditional face analysis tasks (e.g. gender analysis) can be effectively solved by a Look-Up-Table approach given a large-scale face data set.

Abstract: The present invention overcomes the limitations of the prior art by performing facial landmark localization in a coarse-to-fine manner with a cascade of neural network levels, and enforcing geometric constraints for each of the neural network levels. In one approach, the neural network levels may be implemented with deep convolutional neural network. One aspect concerns a system for localizing landmarks on face images. The system includes an input for receiving a face image, and an output for presenting landmarks identified by the system. Neural network levels are coupled in a cascade from the input to the output for the system. Each neural network level produces an estimate of landmarks. The estimate of landmarks is more refined than an estimate of landmark of a previous neural network level.

Abstract: Face representation is a crucial step of face recognition systems. An optimal face representation should be discriminative, robust, compact, and very easy to implement. While numerous hand-crafted and learning-based representations have been proposed, considerable room for improvement is still present. A very easy-to-implement deep learning framework for face representation is presented. The framework bases on pyramid convolutional neural network (CNN). The pyramid CNN adopts a greedy-filter-and-down-sample operation, which enables the training procedure to be very fast and computation efficient. In addition, the structure of Pyramid CNN can naturally incorporate feature sharing across multi-scale face representations, increasing the discriminative ability of resulting representation.

Abstract: A deep learning framework jointly optimizes the compactness and discriminative ability of face representations. The compact representation can be as compact as 32 bits and still produce highly discriminative performance. In another aspect, based on the extreme compactness, traditional face analysis tasks (e.g. gender analysis) can be effectively solved by a Look-Up-Table approach given a large-scale face data set.

Abstract: Face representation is a crucial step of face recognition systems. An optimal face representation should be discriminative, robust, compact, and very easy to implement. While numerous hand-crafted and learning-based representations have been proposed, considerable room for improvement is still present. A very easy-to-implement deep learning framework for face representation is presented. The framework bases on pyramid convolutional neural network (CNN). The pyramid CNN adopts a greedy-filter-and-down-sample operation, which enables the training procedure to be very fast and computation efficient. In addition, the structure of Pyramid CNN can naturally incorporate feature sharing across multi-scale face representations, increasing the discriminative ability of resulting representation.

Abstract: The present invention overcomes the limitations of the prior art by performing facial landmark localization in a coarse-to-fine manner with a cascade of neural network levels, and enforcing geometric constraints for each of the neural network levels. In one approach, the neural network levels may be implemented with deep convolutional neural network. One aspect concerns a system for localizing landmarks on face images. The system includes an input for receiving a face image, and an output for presenting landmarks identified by the system. Neural network levels are coupled in a cascade from the input to the output for the system. Each neural network level produces an estimate of landmarks. The estimate of landmarks is more refined than an estimate of landmark of a previous neural network level.

Abstract: A staple remover having a retractable pair of pliers is provided. The pair of pliers are capable of a retracted position and an extended position. In the extended position, the pliers may be used to remove a partially removed staple or staple fragment.

Abstract: Cutting device for cutting objects, such as leaves, twigs, grass-like plants, fibers, hairs, and the like, having two sets of internally coupled blades, with at least one set of blades being static or dynamically formed whole spiral shape, and the blades having relative rotation therebetween for rotation, oscillation along the axes, rotational oscillation around the axes, or combinations of these motions, to create cutting actions such as shearing, sawing, or a combination of shearing and sawing, with an integrated function of mulching the cuttings generated by the cutting actions.