公开(公告)号：US20250095182A1

公开(公告)日：2025-03-20

申请号：US18468656

申请日：2023-09-15

Applicant: QUALCOMM Incorporated

Inventor： Jisoo JEONG ,  Hong CAI ,  Babak EHTESHAMI BEJNORDI ,  Risheek GARREPALLI ,  Rajeev YASARLA ,  Fatih Murat PORIKLI

IPC: G06T7/593 ,  G06T7/246 ,  G06T7/285

Abstract: Techniques and systems are provided for image processing. For instance, a process can include correlating a first set of features from a first viewpoint with a second set of features from a second viewpoint at a first time period to generate a first disparity cost volume; correlating a third set of features from the first viewpoint at a second time period with the first set of features to generate a first optical flow cost volume; gating the first disparity cost volume to generate first intermediate disparity information; gating the first optical flow cost volume to generate first intermediate optical flow information; correlating the first set of features, the second set of features, and the first intermediate optical flow information to generate disparity information for output; and correlating the third set of features, the first set of features, and the first intermediate disparity information to generate optical flow information for output.

公开(公告)号：US20240161368A1

公开(公告)日：2024-05-16

申请号：US18460903

申请日：2023-09-05

Applicant: QUALCOMM Incorporated

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

IPC: G06T11/60 ,  G06T3/40 ,  G06T7/12 ,  G06T7/50 ,  G06V10/44

CPC classification number: G06T11/60 ,  G06T3/40 ,  G06T7/12 ,  G06T7/50 ,  G06V10/44

Abstract: Certain aspects of the present disclosure provide techniques and apparatus for regenerative learning to enhance dense predictions. In one example method, an input image is accessed. A dense prediction output is generated based on the input image using a dense prediction machine learning (ML) model, and a regenerated version of the input image is generated. A first loss is generated based on the input image and a corresponding ground truth dense prediction, and a second loss is generated based on the regenerated version of the input image. One or more parameters of the dense prediction ML model are updated based on the first and second losses.

公开(公告)号：US20240177329A1

公开(公告)日：2024-05-30

申请号：US18481050

申请日：2023-10-04

Applicant: QUALCOMM Incorporated

Inventor： Hong CAI ,  Yinhao ZHU ,  Jisoo JEONG ,  Yunxiao SHI ,  Fatih Murat PORIKLI

IPC: G06T7/593 ,  G06T3/40 ,  G06T7/246 ,  G06T7/579

CPC classification number: G06T7/593 ,  G06T3/40 ,  G06T7/248 ,  G06T7/579 ,  G06T2207/10012 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: Systems and techniques are provided for processing sensor data. For example, a process can include determining, using a trained machine learning system, a predicted depth map for an image, the predicted depth map including a respective predicted depth value for each pixel of the image. The process can further include obtaining depth values for the image, the depth values including depth values for less than all pixels of the image from a tracker configured to determine the depth values based on one or more feature points between frames. The process can further include scaling the predicted depth map for the image using and the depth values. The output of the process can be scale-correct depth prediction values.

公开(公告)号：US20240020848A1

公开(公告)日：2024-01-18

申请号：US18349771

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: G06T7/168

CPC classification number: G06T7/168 ,  G06T2207/20132

Abstract: Systems and techniques are provided for processing one or more images. For instance, according to some aspects of the disclosure, a method may include obtaining an unlabeled image and generating at least one transformed image based on the unlabeled image. The method may include processing the unlabeled image using a pre-trained semantic segmentation model to generate a first segmentation output. The method may further include processing the at least one transformed image using the pre-trained semantic segmentation model to generate at least a second segmentation output. The method may include fine-tuning, based on the first segmentation output and at least the second segmentation output, one or more parameters of the pre-trained semantic segmentation model.

公开(公告)号：US20230004812A1

公开(公告)日：2023-01-05

申请号：US17808949

申请日：2022-06-24

Applicant: QUALCOMM Incorporated

Inventor： Shubhankar Mangesh BORSE ,  Hong CAI ,  Yizhe ZHANG ,  Fatih Murat PORIKLI

IPC: G06N3/08 ,  G06K9/62

Abstract: Certain aspects of the present disclosure provide techniques for training neural networks using hierarchical supervision. An example method generally includes training a neural network with a plurality of stages using a training data set and an initial number of classification clusters into which data in the training data set can be classified. A cluster-validation set performance metric is generated for each stage based on a reduced number of classification clusters relative to the initial number of classification clusters and a validation data set. A number of classification clusters to implement at each stage is selected based on the cluster-validation set performance metric and an angle selected relative to the cluster-validation set performance metric for a last stage of the neural network. The neural network is retrained based on the training data set and the selected number of classification clusters for each stage, and the trained neural network is deployed.

公开(公告)号：US20240303841A1

公开(公告)日：2024-09-12

申请号：US18538869

申请日：2023-12-13

Applicant: QUALCOMM Incorporated

Inventor： Rajeev YASARLA ,  Hong CAI ,  Jisoo JEONG ,  Risheek GARREPALLI ,  Yunxiao SHI ,  Fatih Murat PORIKLI

IPC: G06T7/50 ,  G06T7/246 ,  G06T11/60 ,  G06V10/44 ,  G06V10/62

CPC classification number: G06T7/50 ,  G06T7/246 ,  G06T11/60 ,  G06V10/44 ,  G06V10/62

Abstract: Disclosed are systems and techniques for capturing images (e.g., using a monocular image sensor) and detecting depth information. According to some aspects, a computing system or device can generate a feature representation of a current image and update accumulated feature information for storage in a memory based on a feature representation of a previous image and optical flow information of the previous image. The accumulated feature information can include accumulated image feature information associated with a plurality of previous images and accumulated optical flow information associated of the plurality of previous images. The computing system or device can obtain information associated with relative motion of the current image based on the accumulated feature information and the feature representation of the current image. The computing system or device can estimate depth information for the current image based on the information associated with the relative motion and the accumulated feature information.

公开(公告)号：US20240169542A1

公开(公告)日：2024-05-23

申请号：US18346470

申请日：2023-07-03

Applicant: QUALCOMM Incorporated

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

IPC: G06T7/10 ,  G06T5/20 ,  G06T5/50 ,  G06V10/44 ,  G06V10/80

CPC classification number: G06T7/10 ,  G06T5/20 ,  G06T5/50 ,  G06V10/44 ,  G06V10/806 ,  G06T2207/20221

Abstract: Techniques and systems are provided for generating one or more segmentations masks. For instance, a process may include generating a delta image based on a difference between a current image and a prior image. The process may further include processing, using a transform operation, the delta image and features representing the prior image to generate a transformed feature representation of the prior image. The process may include combining the transformed feature representation of the prior image with features representing the current image to generate a combined feature representation of the current image. The process may further include generating, based on the combined feature representation of the current image, a segmentation mask for the current image.

公开(公告)号：US20240144589A1

公开(公告)日：2024-05-02

申请号：US18177028

申请日：2023-03-01

Applicant: QUALCOMM Incorporated

Inventor： Minghua LIU ,  Yinhao ZHU ,  Hong CAI ,  Fatih Murat PORIKLI ,  Hao SU

IPC: G06T17/00 ,  G06T7/12 ,  G06V10/25 ,  G06V20/70

CPC classification number: G06T17/00 ,  G06T7/12 ,  G06V10/25 ,  G06V20/70 ,  G06T2207/10028 ,  G06V2201/07

Abstract: Systems and techniques are provided for part segmentation. For example, a process for performing part segmentation can include obtaining a three-dimensional capture of an object. The method can include generating one or more two-dimensional images of the object from the three-dimensional capture of the object. The method can further include processing the one or more two-dimensional images of the object to generate at least one two-dimensional bounding box associated with a part of the object. The method can include performing three-dimensional part segmentation of the part of the object based on a three-dimensional point cloud generated from the one or more two-dimensional images of the object and the at least one two-dimensional bounding box and based on semantically labeled super points which are merged into subgroups associated with the part of the object.

公开(公告)号：US20230298142A1

公开(公告)日：2023-09-21

申请号：US17655427

申请日：2022-03-18

Applicant: QUALCOMM Incorporated

Inventor： Jamie Menjay LIN ,  Diaa H J BADAWI ,  Hong CAI ,  Fatih Murat PORIKLI

IPC: G06T5/00 ,  G06T7/194 ,  G06T5/50

CPC classification number: G06T5/003 ,  G06T5/002 ,  G06T7/194 ,  G06T5/005 ,  G06T5/50 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: Certain aspects of the present disclosure provide techniques for machine learning-based deblurring. An input image is received, and a deblurred image is generated based on the input image using a neural network, comprising: generating a feature tensor by processing the input image using a first portion of the neural network, generating a motion mask by processing the feature tensor using a motion portion of the neural network, and generating the deblurred image by processing the feature tensor and the motion mask using a deblur portion of the neural network.

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.