公开(公告)号：US20250148628A1

公开(公告)日：2025-05-08

申请号：US18633302

申请日：2024-04-11

Applicant: QUALCOMM Incorporated

Inventor： Yunxiao SHI ,  Hong CAI ,  Manish Kumar SINGH ,  Shizhong Steve HAN ,  Yinhao ZHU ,  Fatih Murat PORIKLI

IPC: G06T7/50 ,  G06T3/40 ,  G06V10/44

Abstract: Systems and techniques are provided for generating depth information from one or more images. For example, a process can include obtaining a first depth map corresponding to an input comprising an image of the one or more images and a sparse depth measurement. A three-dimensional (3D) point cloud can be generated based on the first depth map and multi-scale visual features of the input, wherein the 3D point cloud includes a plurality of 3D point features uplifted from the multi-scale visual features. At least a portion of the plurality of 3D point features can be processed using one or more self-attention layers to generate refined 3D point features. A two-dimensional (2D) projection of the refined 3D point features can be generated and a second depth map can be generated based on the 2D projection of the refined 3D point features.

公开(公告)号：US20250054168A1

公开(公告)日：2025-02-13

申请号：US18448845

申请日：2023-08-11

Applicant: QUALCOMM Incorporated

Inventor： Yunxiao SHI ,  Hong CAI ,  Fatih Murat PORIKLI

IPC: G06T7/50

Abstract: A processor-implemented method for attention-based depth completion includes receiving, by an artificial neural network (ANN), an input. The input includes an image and a sparse depth measurement. The ANN extracts multi-scale visual features of the input. The ANN applies a self-attention mechanism to the multi-scale visual features to generate a set of attended multi-scale visual features. The ANN generates a dense depth map based on the set of attended multi-scale visual features.

公开(公告)号：US20240428576A1

公开(公告)日：2024-12-26

申请号：US18613263

申请日：2024-03-22

Applicant: QUALCOMM Incorporated

Inventor： Tianyu JIANG ,  Manish Kumar SINGH ,  Hsin-Pai CHENG ,  Hong CAI ,  Mingu LEE ,  Kartikeya BHARDWAJ ,  Christopher LOTT ,  Fatih Murat PORIKLI

IPC: G06V10/82 ,  G06V10/70 ,  G06V10/77

Abstract: Certain aspects of the present disclosure provide techniques and apparatus for improved machine learning. A transformed version of image pixels is accessed as input to an attention layer of a machine learning model. A number of local attention operations to apply, in one transformer, to the transformed version of image pixels is selected based at least in part on a size of the transformed version of image pixels. A transformer output for the attention layer of the machine learning model is generated based on applying the number of local attention operations and at least one global attention operation to the transformed version of image pixels.

公开(公告)号：US20240412493A1

公开(公告)日：2024-12-12

申请号：US18537404

申请日：2023-12-12

Applicant: QUALCOMM Incorporated

Inventor： Risheek GARREPALLI ,  Yunxiao SHI ,  Hong CAI ,  Yinhao ZHU ,  Shubhankar Mangesh BORSE ,  Jisoo JEONG ,  Debasmit DAS ,  Manish Kumar SINGH ,  Rajeev YASARLA ,  Shizhong Steve HAN ,  Fatih Murat PORIKLI

IPC: G06V10/776 ,  G06T7/50 ,  G06V10/764 ,  G06V10/82 ,  G06V20/70

Abstract: Systems and techniques are provided for processing image data. According to some aspects, a computing device can generate a gradient (e.g., a classifier gradient using a trained classifier) associated with a current sample. The computing device can combine the gradient with an iterative model estimated score function or data associated with the current sample to generate a score function estimate. The computing device can predict, using the diffusion machine learning model and based on the score function estimate, a new sample.

公开(公告)号：US20240404093A1

公开(公告)日：2024-12-05

申请号：US18327380

申请日：2023-06-01

Applicant: QUALCOMM Incorporated

Inventor： Jisoo JEONG ,  Hong CAI ,  Risheek GARREPALLI ,  Fatih Murat PORIKLI ,  Mathew SAM ,  Khalid TAHBOUB ,  Bing HAN

IPC: G06T7/593

Abstract: Systems and techniques are provided for generating disparity information from two or more images. For example, a process can include obtaining first disparity information corresponding to a pair of images, the pair of images including a first image of a scene and a second image of the scene. The process can include obtaining confidence information associated with the first disparity information. The process can include processing, using a machine learning network, the first disparity information and the confidence information to generate second disparity information corresponding to the pair of images. The process can include combining, based on the confidence information, the first disparity information with the second disparity information to generate a refined disparity map corresponding to the pair of images.

公开(公告)号：US20240303913A1

公开(公告)日：2024-09-12

申请号：US18180797

申请日：2023-03-08

Applicant: QUALCOMM Incorporated

Inventor： Yinhao ZHU ,  Rui ZHU ,  Hong CAI ,  Fatih Murat PORIKLI

IPC: G06T15/50 ,  G06T7/593

CPC classification number: G06T15/506 ,  G06T7/593

Abstract: Systems and techniques are provided for physical-based light estimation for inverse rendering of indoor scenes. For example, a computing device can obtain an estimated scene geometry based on a multi-view observation of a scene. The computing device can further obtain a light emission mask based on the multi-view observation of the scene. The computing device can also obtain an emitted radiance field based on the multi-view observation of the scene. The computing device can then determine, based on the light emission mask and the emitted radiance field, a geometry of at least one light source of the estimated scene geometry.

公开(公告)号：US20240161312A1

公开(公告)日：2024-05-16

申请号：US18477493

申请日：2023-09-28

Applicant: QUALCOMM Incorporated

Inventor： Jisoo JEONG ,  Risheek GARREPALLI ,  Hong CAI ,  Fatih Murat PORIKLI

IPC: G06T7/246

CPC classification number: G06T7/248 ,  G06T2207/10016 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: A computer-implemented method includes generating a first augmented frame by combining a first image and a first frame of a first frame pair. The computer-implemented method also includes generating, via an optical flow estimation model, a first flow estimation based on a second frame of the first frame pair and the first augmented frame. The computer-implemented method further includes updating one or both of parameters or weights of the optical flow estimation model based on a first loss between the first flow estimation and a training target.

公开(公告)号：US20240020844A1

公开(公告)日：2024-01-18

申请号：US18349726

申请日：2023-07-10

Applicant: QUALCOMM Incorporated

Inventor： Debasmit DAS ,  Shubhankar Mangesh BORSE ,  Hyojin PARK ,  Kambiz AZARIAN YAZDI ,  Hong CAI ,  Risheek GARREPALLI ,  Fatih Murat PORIKLI

IPC: G06T7/11

CPC classification number: G06T7/11 ,  G06T2207/20081 ,  G06T2207/20004

Abstract: Systems and techniques are provided for processing data (e.g., image data). For instance, according to some aspects of the disclosure, a method may include receiving, at a transformer of a machine learning system, learnable queries, keys, and values obtained from a feature map of a segmentation model of the machine learning system. The method may further include learning, via the transformer, a mapping between an unsupervised output and a supervised output of the segmentation model based on the feature map.