公开(公告)号：US20240005628A1

公开(公告)日：2024-01-04

申请号：US18031064

申请日：2020-11-19

Applicant: Intel Corporation

Inventor： Dongqi CAI ,  Anbang YAO ,  Yikai WANG ,  Ming LU ,  Yurong CHEN

IPC: G06V10/44 ,  G06V10/80 ,  G06V10/82

CPC classification number: G06V10/454 ,  G06V10/82 ,  G06V10/811 ,  G06V10/806

Abstract: Techniques related to bidirectional compact deep fusion networks for multimodal image inputs are discussed. Such techniques include applying a shared convolutional layer and independent batch normalization layers to input volumes for each modality and fusing features from the resultant output volumes in both directions across the modalities.

公开(公告)号：US20250045573A1

公开(公告)日：2025-02-06

申请号：US18709267

申请日：2022-03-03

Applicant: Intel Corporation

Inventor： Anbang YAO ,  Yikai WANG ,  Zhaole SUN ,  Yi YANG ,  Feng CHEN ,  Zhuo WANG ,  Shandong WANG ,  Yurong CHEN

IPC: G06N3/0495 ,  G06N3/0464

Abstract: The disclosure relates to decimal-bit network quantization of CNN models. Methods, apparatus, systems, and articles of manufacture for quantizing a CNN model includes, for a convolutional layer of the CNN model: allocating a 1-bit convolutional kernel subset to the convolutional layer, wherein the convolutional layer includes 32-bit or 16-bit floating-point convolutional kernels with a size of K×K and the 1-bit convolutional kernel subset includes 2N 1-bit convolutional kernel candidates with the size of K×K, 1≤N

公开(公告)号：US20230386072A1

公开(公告)日：2023-11-30

申请号：US18031564

申请日：2020-12-01

Applicant: Intel Corporation

Inventor： Anbang YAO ,  Yangyuxuan KANG ,  Shandong WANG ,  Ming LU ,  Yurong CHEN ,  Wenjian SHAO ,  Yikai WANG ,  Haojun XU ,  Chao YU ,  Chong WONG

IPC: G06T7/73 ,  G06V40/10

CPC classification number: G06T7/73 ,  G06V40/103 ,  G06T2207/30196 ,  G06T2207/20084 ,  G06V10/82

Abstract: Techniques related to 3D pose estimation from a 2D input image are discussed. Such techniques include incrementally adjusting an initial 3D pose generated by applying a lifting network to a detected 2D pose in the 2D input image by projecting each current 3D pose estimate to a 2D pose projection, applying a residual regressor to features based on the 2D pose projection and the detected 2D pose, and combining a 3D pose increment from the residual regressor to the current 3D pose estimate.

公开(公告)号：US20230343068A1

公开(公告)日：2023-10-26

申请号：US17918080

申请日：2020-06-15

Applicant: Intel Corporation

Inventor： Anbang YAO ,  Yikai WANG ,  Ming LU ,  Shandong WANG ,  Feng CHEN

IPC: G06V10/764 ,  G06V10/32 ,  G06V10/44 ,  G06V10/774 ,  G06V10/82

CPC classification number: G06V10/764 ,  G06V10/32 ,  G06V10/454 ,  G06V10/774 ,  G06V10/82

Abstract: Techniques related to implementing and training image classification networks are discussed. Such techniques include applying shared convolutional layers to input images regardless of resolution and applying normalization selectively based on the input image resolution. Such techniques further include training using mixed image size parallel training and mixed image size ensemble distillation.