公开(公告)号：US20240005547A1

公开(公告)日：2024-01-04

申请号：US17750785

申请日：2022-05-23

Applicant: NVIDIA Corporation

Inventor： Yunzhi Lin ,  Jonathan Tremblay ,  Stephen Walter Tyree ,  Stanley Thomas Birchfield

IPC: G06T7/70 ,  G06T7/277

CPC classification number: G06T7/70 ,  G06T7/277 ,  G06T2207/20081 ,  G06T2207/10016 ,  G06T2207/20084 ,  G06T2207/10024

Abstract: Apparatuses, systems, and techniques to determined a pose of an object from a plurality of images. In at least one embodiment, the pose of an object is determined from at least two images of a video sequence using one or more neural networks, in which the neural network produces a distribution of pose information that is filtered to determine the current pose.

公开(公告)号：US10783393B2

公开(公告)日：2020-09-22

申请号：US16006709

申请日：2018-06-12

Applicant: NVIDIA Corporation

Inventor： Pavlo Molchanov ,  Stephen Walter Tyree ,  Jan Kautz ,  Sina Honari

IPC: G06K9/00 ,  G06K9/62 ,  G06K9/46 ,  G06N3/08 ,  G06K9/66 ,  G06N3/04

Abstract: A method, computer readable medium, and system are disclosed for sequential multi-tasking to generate coordinates of landmarks within images. The landmark locations may be identified on an image of a human face and used for emotion recognition, face identity verification, eye gaze tracking, pose estimation, etc. A neural network model processes input image data to generate pixel-level likelihood estimates for landmarks in the input image data and a soft-argmax function computes predicted coordinates of each landmark based on the pixel-level likelihood estimates.

公开(公告)号：US10157309B2

公开(公告)日：2018-12-18

申请号：US15402128

申请日：2017-01-09

Applicant: NVIDIA Corporation

Inventor： Pavlo Molchanov ,  Xiaodong Yang ,  Shalini De Mello ,  Kihwan Kim ,  Stephen Walter Tyree ,  Jan Kautz

IPC: G06K9/00 ,  G06K9/62 ,  G06N3/04 ,  G06N3/08

Abstract: A method, computer readable medium, and system are disclosed for detecting and classifying hand gestures. The method includes the steps of receiving an unsegmented stream of data associated with a hand gesture, extracting spatio-temporal features from the unsegmented stream by a three-dimensional convolutional neural network (3DCNN), and producing a class label for the hand gesture based on the spatio-temporal features.

公开(公告)号：US20180114114A1

公开(公告)日：2018-04-26

申请号：US15786406

申请日：2017-10-17

Applicant: NVIDIA Corporation

Inventor： Pavlo Molchanov ,  Stephen Walter Tyree ,  Tero Tapani Karras ,  Timo Oskari Aila ,  Jan Kautz

IPC: G06N3/08

CPC classification number: G06N3/082 ,  G06N3/0454 ,  G06N3/084

Abstract: A method, computer readable medium, and system are disclosed for neural network pruning. The method includes the steps of receiving first-order gradients of a cost function relative to layer parameters for a trained neural network and computing a pruning criterion for each layer parameter based on the first-order gradient corresponding to the layer parameter, where the pruning criterion indicates an importance of each neuron that is included in the trained neural network and is associated with the layer parameter. The method includes the additional steps of identifying at least one neuron having a lowest importance and removing the at least one neuron from the trained neural network to produce a pruned neural network.