公开(公告)号：US20230410487A1

公开(公告)日：2023-12-21

申请号：US18250498

申请日：2020-11-30

Applicant: Intel Corporation

Inventor： Lidan Zhang ,  Qi She ,  Ping Guo ,  Yimin Zhang

IPC: G06V10/778 ,  G06V20/40 ,  G06V10/82 ,  G06V40/20

CPC classification number: G06V10/778 ,  G06V20/41 ,  G06V20/44 ,  G06V10/82 ,  G06V40/20 ,  G06V20/46

Abstract: Performing online learning for a model to detect unseen actions in an action recognition system is disclosed. The method includes extracting semantic features in a semantic domain from semantic action labels, transforming the semantic features from the semantic domain into mixed features in a mixed domain, and storing the mixed features in a feature database. The method further includes extracting visual features in a visual domain from a video stream and determining if the visual features indicate an unseen action in the video stream. If no unseen action is determined, applying an offline classification model to the visual features to identify seen actions, assigning identifiers to the identified seen actions, transforming the visual features from the visual domain into mixed features in the mixed domain, and storing the mixed features and seen action identifiers in the feature database. If an unseen action is determined, transforming the visual features from the visual domain into mixed features in the mixed domain, applying a continual learner model to mixed features from the feature database to identify unseen actions in the video stream, assigning identifiers to the identified unseen actions, and storing the unseen action identifiers in the feature database.

公开(公告)号：US12198460B2

公开(公告)日：2025-01-14

申请号：US17635792

申请日：2019-09-16

Applicant: INTEL CORPORATION

Inventor： Lidan Zhang ,  Qi She ,  Ping Guo

IPC: G06V40/10 ,  G06N3/044 ,  G06N3/048 ,  G06T7/12 ,  G06T7/246 ,  G06T7/73 ,  G06V10/82 ,  G06Q50/00

Abstract: Systems, methods, apparatuses, and computer program products to provide stochastic trajectory prediction using social graph networks. An operation may comprise determining a first feature vector describing destination features of a first person depicted in an image, generating a directed graph for the image based on all people depicted in the image, determining, for the first person, a second feature vector based on the directed graph and the destination features, sampling a value of a latent variable from a learned prior distribution, the latent variable to correspond to a first time interval, and generating, based on the sampled value and the feature vectors by a hierarchical long short-term memory (LSTM) executing on a processor, an output vector comprising a direction of movement and a speed of the direction of movement of the first person at a second time interval, subsequent to the first time interval.

公开(公告)号：US20220138555A1

公开(公告)日：2022-05-05

申请号：US17088328

申请日：2020-11-03

Applicant: Intel Corporation

Inventor： Lidan Zhang ,  Lei Zhu ,  Qi She ,  Ping Guo

IPC: G06N3/08

Abstract: Examples methods, apparatus, and articles of manufacture corresponding to a spectral nonlocal block have been disclosed. An example apparatus includes a first convolution filter to perform a first convolution using input features and first weighted kernels to generate first weighted input features, the input features corresponding to data of a neural network; an affinity matrix generator to: perform a second convolution using the input features and second weighted kernels to generate second weighted input features; perform a third convolution using the input features and third weighted kernels to generate third weighted input features; and generate an affinity matrix based on the second and third weighted input features; a second convolution filter to perform a fourth convolution using the first weighted input features and fourth weighted kernels to generate fourth weighted input features; and a accumulator to transmit output features corresponding to a spectral nonlocal operator.

公开(公告)号：US20220292867A1

公开(公告)日：2022-09-15

申请号：US17635792

申请日：2019-09-16

Applicant: INTEL CORPORATION

Inventor： Lidan ZHANG ,  Qi She ,  Ping Guo

IPC: G06V40/10 ,  G06N3/04 ,  G06T7/73 ,  G06T7/12 ,  G06T7/246 ,  G06V10/82

Abstract: Systems, methods, apparatuses, and computer program products to provide stochastic trajectory prediction using social graph networks. An operation may comprise determining a first feature vector describing destination features of a first person depicted in an image, generating a directed graph for the image based on all people depicted in the image, determining, for the first person, a second feature vector based on the directed graph and the destination features, sampling a value of a latent variable from a learned prior distribution, the latent variable to correspond to a first time interval, and generating, based on the sampled value and the feature vectors by a hierarchical long short-term memory (LSTM) executing on a processor, an output vector comprising a direction of movement and a speed of the direction of movement of the first person at a second time interval, subsequent to the first time interval.