Abstract: Embodiments of the disclosure discloses a method, apparatus, device and storage medium for image generation. The method includes obtaining a first human body image comprising a target human body and a first clothing image comprising target clothing; performing key point extraction, portrait segmentation and human body part segmentation on the first human body image respectively, to obtain a key point feature image, portrait segmented image and human body part segmented image; inputting the key point feature image, the portrait segmented image, human body part segmented image and first clothing image into a transformation model, to obtain a transformed second clothing image; and inputting the second clothing image, first human body image, key point feature image, portrait segmented image and human body part segmented image into a merging model, to obtain a second human body image, wherein the target human body in the second human body image wears the target clothing.

Abstract: The disclosure relates to a method, apparatus, device and storage medium for image processing. The method includes performing a smearing process on a target facial organ in a facial image to be process by a pretrained smearing model, to obtain a smeared facial image corresponding to the facial image to be processed. By performing the smearing process on the target facial organ in the facial image to be processed to generate the corresponding smeared facial image, it can improve the interest of the image.

Abstract: The embodiments of the present disclosure relate to an image generation method, apparatus, device, and medium. The method includes: obtaining an initial image of a target object, where the initial image is an image in a first image style; inputting the initial image into a first machine learning model; and obtaining a target image of the target object based on an output result of the first machine learning model, where the target image is an image in a second image style. The first machine learning model is obtained based on a second machine learning model obtained based on training first sample images of the target object and second sample images of the target object. The first sample image and the second sample image are respectively images obtained by rendering simulation models of the target object in different states based on rendering parameters in the first and second image styles.

Abstract: The present disclosure relates to a device, method and computer readable medium for sending an emergency message. A device for sending an emergency message through an apparatus installed with at least one communication application, the device comprises: a memory having instructions stored therein; a processor configured to execute the instructions stored on the memory so that the processor performs the following operations: receiving an emergency signal from a user; transmitting an emergency message to the at least one communication application in response to the received emergency signal; and sending, through the at least one communication application, the emergency message to contacts of the at least one communication application.

Abstract: A reconstruction system for digital signals processed by the laplacian pyramid including a master lifting-based parameterization reconstruction scheme. The system also involves the design of low-complexity FIR linear-phase integer-coefficient filtering operators for lapacian pyramid decimation and interpolation stages that deliver a minimum mean-squared error reconstruction.

Abstract: A method of making a photonic fabric display includes wrapping photonic fibers with a yarn, weaving the wrapped photonic fibers to form a fabric, printing a pattern on the fabric, surface treating the fabric, and coupling the photonic fibers with a light source to form a photonic fabric display.

Abstract: A reconstruction system for digital signals processed by the laplacian pyramid including a master lifting-based parameterization reconstruction scheme. The system also involves the design of low-complexity FIR linear-phase integer-coefficient filtering operators for lapacian pyramid decimation and interpolation stages that deliver a minimum mean-squared error reconstruction.

Abstract: A photonic fabric display wherein graphic patterns, color, luminescence intensity, and light self-amplification are controllable. Incorporated in the fabric display are a number of photonic fibers which contain a converter either coated on a surface of the photonic fibers or inside said photonic fibers and a light source, such as LEDs, is connected to the end of the photonic fibers by using an efficient coupler.

Abstract: A method of making a photonic fabric display includes wrapping photonic fibers with a yarn, weaving the wrapped photonic fibers to form a fabric, printing a pattern on the fabric, surface treating the fabric, and coupling the photonic fibers with a light source to form a photonic fabric display.

Abstract: This invention relates to the design and implementation of a large family of fast, efficient, hardware-friendly fixed-point multiplierless inverse discrete cosine transforms (IDCT) and the corresponding forward transform counterparts. All of the proposed structures comprises of butterflies and dyadic-rational lifting steps that can be implemented using only shift-and-add operations. The approach also allows the computational scalability with different accuracy-versus-complexity trade-offs. Furthermore, the lifting construction allows a simple construction of the corresponding multiplierless forward DCT, providing bit-exact reconstruction if properly pairing with our proposed IDCT. With appropriately-chosen parameters, all of the disclosed structures can easily pass IEEE-1180 test.