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    Universal Loss-Error-Aware Quantization for Deep Neural Networks with Flexible Ultra-Low-Bit Weights and Activations
    2.
    发明申请
    Universal Loss-Error-Aware Quantization for Deep Neural Networks with Flexible Ultra-Low-Bit Weights and Activations 有权

    公开(公告)号：US20220129759A1

    公开(公告)日：2022-04-28

    申请号：US17441622

    申请日：2019-06-26

    Applicant: Intel Corporation

    Inventor： Anbang YAO ,  Aojun ZHOU ,  Dawei SUN ,  Dian GU ,  Yurong CHEN

    IPC: G06N3/08 ,  G06T9/00 ,  G06N3/04

    Abstract: Apparatuses, methods, and GPUs are disclosed for universal loss-error-aware quantization (ULQ) of a neural network (NN). In one example, an apparatus includes data storage to store data including activation sets and weight sets, and a network processor coupled to the data storage. The network processor is configured to implement the ULQ by constraining a low-precision NN model based on a full-precision NN model, to perform a loss-error-aware activation quantization to quantize activation sets into ultra-low-bit versions with given bit-width values, to optimize the NN with respect to a loss function that is based on the full-precision NN model, and to perform a loss-error-aware weight quantization to quantize weight sets into ultra-low-bit versions.

    3D FACIAL CAPTURE AND MODIFICATION USING IMAGE AND TEMPORAL TRACKING NEURAL NETWORKS
    3.
    发明申请
    3D FACIAL CAPTURE AND MODIFICATION USING IMAGE AND TEMPORAL TRACKING NEURAL NETWORKS 有权

    公开(公告)号：US20210104086A1

    公开(公告)日：2021-04-08

    申请号：US16971132

    申请日：2018-06-14

    Applicant: Intel Corporation

    Inventor： Shandong WANG ,  Ming LU ,  Anbang YAO ,  Yurong CHEN

    IPC: G06T13/40 ,  G06N3/04 ,  G06N3/08 ,  G06K9/00 ,  G06T19/20 ,  G06K9/62

    Abstract: Techniques related to capturing 3D faces using image and temporal tracking neural networks and modifying output video using the captured 3D faces are discussed. Such techniques include applying a first neural network to an input vector corresponding to a first video image having a representation of a human face to generate a morphable model parameter vector, applying a second neural network to an input vector corresponding to a first and second temporally subsequent to generate a morphable model parameter delta vector, generating a 3D face model of the human face using the morphable model parameter vector and the morphable model parameter delta vector, and generating output video using the 3D face model.

    DYNAMIC TRIPLET CONVOLUTION FOR CONVOLUTIONAL NEURAL NETWORKS
    5.
    发明申请
    DYNAMIC TRIPLET CONVOLUTION FOR CONVOLUTIONAL NEURAL NETWORKS 有权

    公开(公告)号：US20250068891A1

    公开(公告)日：2025-02-27

    申请号：US18724510

    申请日：2022-02-18

    Applicant: Intel Corporation

    Inventor： Dongqi CAI ,  Anbang YAO ,  Chao LI ,  Yurong CHEN ,  Wenjian SHAO

    IPC: G06N3/0464

    Abstract: Methods, apparatus, systems and articles of manufacture (e.g., physical storage media) to implement dynamic triplet convolution for convolutional neural networks are disclosed. An example apparatus disclosed herein for a convolutional neural network is to calculate one or more scalar kernels based on an input feature map applied to a layer of the convolutional neural network, ones of the one or more scalar kernels corresponding to respective dimensions of a static multidimensional convolutional filter associated with the layer of the convolutional neural network. The disclosed example apparatus is also to scale elements of the static multidimensional convolutional filter along a first one of the dimensions based on a first one of the one or more scalar kernels corresponding to the first one of the dimensions to determine a dynamic multidimensional convolutional filter associated with the layer of the convolutional neural network.

    METHOD AND SYSTEM OF IMAGE HASHING OBJECT DETECTION FOR IMAGE PROCESSING
    6.
    发明公开
    METHOD AND SYSTEM OF IMAGE HASHING OBJECT DETECTION FOR IMAGE PROCESSING 审中-公开

    公开(公告)号：US20230368493A1

    公开(公告)日：2023-11-16

    申请号：US18030024

    申请日：2020-11-13

    Applicant: Intel Corporation

    Inventor： Yuqing HOU ,  Xiaolong LIU ,  Anbang YAO ,  Yurong CHEN

    IPC: G06V10/764 ,  G06V10/82 ,  G06V10/776

    CPC classification number: G06V10/764 ,  G06V10/82 ,  G06V10/776

    Abstract: A method and system of image hashing object detection for image processing are provided. The method comprises the following steps: obtaining image head class input data and image tail class input data differentiated from the head class input data and respectively of two images each of an object to be classified; respectively inputting the head and tail class input data into two separate parallel representation neural networks being trained to respectively generate head and tail features, wherein the representation neural networks share at least some representation weights used to form the head and tail features; inputting the head and tail features into at least one classifier neural network to generate class-related data; generating a class-balanced loss of at least one of the classes of the class-related data comprising factoring an effective number of samples of individual classes; and rebalancing an output sample distribution among the classes at the representation neural networks, classifier neural networks, or both by using the class-balanced loss.

    TECHNIQUES FOR DENSE VIDEO DESCRIPTIONS
    8.
    发明申请
    TECHNIQUES FOR DENSE VIDEO DESCRIPTIONS 有权

    公开(公告)号：US20220180127A1

    公开(公告)日：2022-06-09

    申请号：US17569725

    申请日：2022-01-06

    Applicant: INTEL CORPORATION

    Inventor： Yurong CHEN ,  Jianguo LI ,  Zhou SU ,  Zhiqiang SHEN

    IPC: G06K9/62 ,  G06F40/169 ,  G06N3/08 ,  G06V20/40

    Abstract: Techniques and apparatus for generating dense natural language descriptions for video content are described. In one embodiment, for example, an apparatus may include at least one memory and logic, at least a portion of the logic comprised in hardware coupled to the at least one memory, the logic to receive a source video comprising a plurality of frames, determine a plurality of regions for each of the plurality of frames, generate at least one region-sequence connecting the determined plurality of regions, apply a language model to the at least one region-sequence to generate description information comprising a description of at least a portion of content of the source video. Other embodiments are described and claimed.

    COMBINATORIAL SHAPE REGRESSION FOR FACE ALIGNMENT IN IMAGES
    9.
    发明申请
    COMBINATORIAL SHAPE REGRESSION FOR FACE ALIGNMENT IN IMAGES 审中-公开

    公开(公告)号：US20180137383A1

    公开(公告)日：2018-05-17

    申请号：US15573631

    申请日：2015-06-26

    Applicant: Intel Corporation

    Inventor： Anbang YAO ,  Yurong CHEN

    IPC: G06K9/32 ,  G06K9/00 ,  G06K9/62

    Abstract: Combinatorial shape regression is described as a technique for face alignment and facial landmark detection in images. As described stages of regression may be built for multiple ferns for a facial landmark detection system. In one example a regression is performed on a training set of images using face shapes, using facial component groups, and using individual face point pairs to learn shape increments for each respective image in the set of images. A fern is built based on this regression. Additional regressions are performed for building additional ferns. The ferns are then combined to build the facial landmark detection system.

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