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：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：US20250148633A1

公开(公告)日：2025-05-08

申请号：US18666502

申请日：2024-05-16

Applicant: QUALCOMM Incorporated

Inventor： Rajeev YASARLA ,  Hong CAI ,  Risheek GARREPALLI ,  Yinhao ZHU ,  Jisoo JEONG ,  Yunxiao SHI ,  Manish Kumar SINGH ,  Fatih Murat PORIKLI

IPC: G06T7/593 ,  G06T7/20

Abstract: Systems and techniques are provided for generating depth information. For example, a process can include obtaining a first feature volume including visual features corresponding to each respective frame included in a first set of frames. A first query generator network can generate reconstruction features associated with a reconstructed feature volume corresponding to the first feature volume. Based on the first feature volume, a second query generator network can generate motion features associated with predicted future motion corresponding to the first feature volume. An initial depth prediction can be generated for each respective frame based on cross-attention between features of a depth prediction decoder, the reconstruction features, and the motion features. A refined depth prediction can be generated for each respective based on cross-attention between the initial depth prediction, the reconstruction features, and the motion features.

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.