Abstract: A method for compressing a 3D medical image includes the steps of receiving a 3D medical image, partitioning the 3D medical image into a plurality of first slices, encoding the plurality of the first slices by a lossy codec into first bitstreams, decoding the first bitstreams by the lossy codec to obtain a plurality of second slices, computing a plurality of residues by comparing the plurality of the first slices and the plurality of the second slices, encoding the plurality of the residues by a lossless codec to obtain a plurality of encoded residues, and outputting the first bitstreams and the plurality of the encoded residues as compressed image data. Each residue corresponds to one of the first slices and its corresponding second slice. Experimental results on prevailing 3D medical image datasets demonstrate that the proposed method achieves promising compression performance and outperforms state-of-the-art methods.

Abstract: There is provided a computer-implemented method for processing a video. The computer-implemented method includes: (a) determining a target frame-level quality required for a frame of the video to be encoded, the determining of the target frame-level quality is based on, at least, a rate-quantization (R-Q) model that relates bit-rate and quantization step size and a quality-quantization model that relates quality measure and the quantization step size; and (b) determining one or more coding parameters for encoding the frame based on the determined target frame-level quality.

Abstract: Embodiments of the present disclosure provide a solution for image/video super resolution. A method for image processing is proposed. The method comprises: receiving a first image with a first resolution and at least one reference image associated with the first image, the first image and the at least one reference image being associated with a same video; determining a difference between the first image and the at least one reference image; and generating a second image with a second resolution based on the difference, the first image and the at least one reference image, the second resolution being higher than the first resolution.

Abstract: Methods and apparatuses are provided for processing video data by using generative face video supplemental enhancement information (SEI) messages. An exemplary method for generating a face picture includes: receiving a bitstream; decoding coded information of the bitstream to obtain a base picture and a supplemental enhancement information (SEI) message; determining whether the SEI message applies to a neural network for generating a face picture; in response to the SEI message applies to the neural network for generating the face picture, determining a mode and a corresponding face information parameter used to code the face picture based on the SEI message; and generating the face picture based on the base picture and the face information parameter by the neural network.

Abstract: The present application provides methods, devices and computer readable media for intrinsic popularity evaluation and content compression based thereon. In an embodiment, there is provided a method of intrinsic popularity evaluation. The method comprises: receiving an image from a social network; and determining an intrinsic popularity score for the image using a deep neural network (DNN) based intrinsic popularity assessment model.

Abstract: The present disclosure provides a central staged combustion chamber with self-excited sweeping oscillating fuel injection nozzles, including an outer housing with a cavity inside, a main stage coaxially disposed with the outer housing, and a pilot stage coaxially disposed with the outer housing. An annular fuel passage is used for connecting a plurality of self-excited sweeping oscillating fuel injection nozzles, and the self-excited sweeping oscillating fuel injection nozzles are suitable for injecting oscillating liquid fuel into a primary swirling passage. The fuel is output in a fan shape through each of the self-excited sweeping oscillating fuel injection nozzles and is dispersed by an incoming flow through the swirling passage, so that the atomization performance and spatial distribution uniformity of the fuel can be greatly improved.

Abstract: A computer-implemented method for processing a video includes: (a) determining, based on one or more rate-distortion models and number of bits for a frame of the video, coding parameters for processing the frame, the coding parameters comprising a rescale parameter r and a video compression model ?, and (b) processing the frame based on the rescale parameter r and the video compression model ? determined in (a) to form at least part of a bitstream of the video.

Abstract: A method for performing detection-based object searches includes receiving a user request indicating a region of interest, a timeframe of interest, or an object of interest. A signal is sent to cause execution of a query to identify object detections based on the user request. A signal representing at least one event identified in response to the query is received. For each event from the at least one event, a thumbnail image is identified based on the user request and using a ranking algorithm. A video frame identified based on the thumbnail image is received, and a video segment associated with the video frame is retrieved, A preview image clip that includes the video frame and the video segment is generated and displayed to a user associated with the user request.

Abstract: A system and a method for processing an image. The system comprises an image gateway arranged to receive an input image showing a scene composed by a combination of a plurality of image portions of the input image, wherein one or more of the plurality of image portions is associated with an exposure level deviated from an optimal exposure level; and an enhancement engine arranged to process the input image by applying an exposure/image relationship to the input image, wherein the exposure/image relationship is arranged to adjust the exposure level of each of the plurality of image portions towards the optimal exposure level; and to generate an enhanced image showing a visual representation of the scene composed by a combination of the plurality of image portions of the input image with an adjusted exposure level.

Abstract: A method implemented by a video coding apparatus includes applying a neural network (NN) filter to an unfiltered sample of a video unit to generate a filtered sample. The NN filter is applied based on a syntax element of the video unit. The method also includes converting between a video media file and a bitstream based on the filtered sample that was generated.

Abstract: A method of encoding a video sequence into a bitstream includes receiving a video sequence; encoding one or more pictures of the video sequence; and generating a bitstream. The encoding includes compressing a reference picture; transforming, based on the reference picture, a plurality of inter pictures associated with the reference picture into facial semantics; and encoding the facial semantics.

Abstract: A system and a method for assessing quality of a high-dynamic range (HDR) image. The system comprises a feature extraction module arranged to extract a plurality of frequency features on a pair of reference image and a distorted image generated based on the reference image; a comparison module arranged to compare a pair of feature maps obtained by processing the extracted frequency features on both the reference image and the distorted image; and a scoring module arrange to output an image quality assessment (IQA) score of the distorted image with reference to the reference image provided; wherein the plurality of frequency features are associated with sensitive information in a human visual system (HVS).

Abstract: A method of decoding a bitstream to output one or more pictures for a video stream, includes: receiving a bitstream; and decoding, using coded information of the bitstream, one or more pictures. The decoding includes: determining, based on an identifying number, whether a face video generative compression scheme is used; in response to a determination that the face video generative compression scheme is used, decoding a supplemental enhancement information (SEI) message, the SEI message comprising facial information; and reconstructing a face picture based on the facial information and a base picture associated with the SEI message.

Abstract: Methods and systems implement input picture data preprocessing for a learning model by picture data blurring based on deep features. Intermediate features are extracted from convolutional layers of a preprocessing model, and each set of intermediate features are fused to yield a fused feature map, and enlarged to input picture size. Based on the fused feature map, the preprocessing model can configure one or more processors of an input preprocessing computing system to, in performing blurring preprocessing computations, emphasize picture data having larger corresponding characteristic values, and deemphasize other picture data.

Abstract: Methods and apparatuses are provided for encoding and decoding video data based on a supplemental enhancement information (SEI) message. An exemplary method includes: generating a reconstrued frame sequence based on a compressed video; decoding a supplemental enhancement information (SEI) message with respect to the reconstrued frame sequence, according to the compressed video; and performing temporal upsampling to the reconstrued frame sequence based on the SEI message by using a neural network.

Abstract: A method for temporal resampling for multi-task machine vision is provided. The method includes receiving a bitstream of a video sequence after temporal resampling; and constructing a target frame from the bitstream using a frame construction model.

Abstract: Two-dimensional face presentation attacks are one of most notorious and pervasive face spoofing types, causing security issues to facial authentication systems. To tackle these issues, a cost-effective face anti-spoofing (FAS) system based on acoustic modality, named as Echo-FAS, is devised, which employs a crafted acoustic signal to probe the presented face. First, a large-scale, high-diversity, acoustic-based FAS database, named as Echo-Spoof, is built. Based upon Echo-Spoof, we design a two-branch framework combining global and local frequency features of the presented face to distinguish live vs. spoofing faces. Echo-FAS has the following merits: (1) it only needs one speaker and one microphone; (2) it can capture three-dimensional geometrical information of the presented face and achieve a remarkable FAS performance; and (3) it can be handily allied with RGB-based FAS models to mitigate the overfitting problem in the RGB modality and make the FAS model more accurate and robust.

Abstract: Methods and apparatuses are provided for processing video data. An exemplary method includes: decompressing a compressed frame to generate a key frame representing a face; generating, for the key frame, a first set of parameters associated with a 3-dimensional (3D) face representation of the face; reconstructing, for each of one or more inter frames, a second set of parameters associated with a 3D face representation of the face according to compressed inter-predicted residuals of the second set of parameters; and generating a video comprising the face based on the key frame, the first set of parameters, and the second set of parameters.

Abstract: A computer-implemented method for facilitating machine-learning based media (e.g., video) compression. The method includes receiving a motion data set associated with motion-related difference between a first image and a second image, and processing the motion data set using a neural network to determine a plurality of motion data subsets. The method also includes processing the plurality of motion data subsets using one or more features associated with the first image to obtain a plurality of motion-warped feature data sets each associated with a respective motion data subset; and processing the plurality of motion-warped feature data sets to facilitate generation of context data for facilitating conditional coding based compression of the second image.

Abstract: A method for processing a screen content video. The screen content video includes a plurality of frames each including a plurality of coding tree units and a plurality of coding units in each of the coding tree units. The method includes performing a coding-tree-unit-based analysis operation on the screen content video to determine content information associated with the screen content video, and performing a rate control operation on the screen content video based on the determined content information to encoding of the screen content video. The content information includes content complexity information associated with the screen content video and temporal importance information associated with the screen content video.