公开(公告)号：US11860977B1

公开(公告)日：2024-01-02

申请号：US17307701

申请日：2021-05-04

Applicant: Amazon Technologies, Inc.

Inventor： Yifan Xing ,  Tianjun Xiao ,  Tong He ,  Yongxin Wang ,  Yuanjun Xiong ,  Wei Xia ,  David Paul Wipf ,  Zheng Zhang ,  Stefano Soatto

IPC: G06F18/2323 ,  G06N20/00 ,  G06F18/2415 ,  G06F18/23213 ,  G06F18/2413

CPC classification number: G06F18/2323 ,  G06F18/23213 ,  G06F18/2415 ,  G06F18/24147 ,  G06N20/00

Abstract: Techniques for performing visual clustering with a hierarchical graph neural network framework including a joint linkage prediction and density estimation graph model are described. Embodiments herein recurrently run the joint linkage prediction and density estimation graph model to generate intermediate clusters in multiple iterations (e.g., until convergence) to obtain a final clustering result. In certain embodiments, for each iteration, the input graph contains nodes that are merged from nodes assigned to intermediate clusters from the previous iteration. By using a small and fixed bandwidth k in each iteration, embodiments herein alleviate the sensitivity to the k selection for different clustering applications. Certain embodiments herein remove the tuning of a different k (e.g., k-bandwidth) for k-nearest neighbor graph construction over different clustering applications.

公开(公告)号：US11272164B1

公开(公告)日：2022-03-08

申请号：US16746313

申请日：2020-01-17

Applicant: Amazon Technologies, Inc.

Inventor： Yifan Xing ,  Yuanjun Xiong ,  Wei Xia ,  Wei Li ,  Shuo Yang ,  Meng Wang

IPC: H04N13/275 ,  G06T7/73 ,  G06N20/00 ,  G06T15/50

Abstract: Techniques for data synthesis for training datasets for machine learning applications are described. A first image of at least an object from a first viewpoint is obtained. The first image having associated first image metadata including a first location of a feature of the object in the first image. A model is generated from the first image, the model including a three-dimensional representation of the object. A second image is generated from the model, the second image including the object from a second viewpoint that is different from the first viewpoint. Second image metadata is generated, the second image metadata including a second location of the feature of the object in the second image, the second location corresponding to the first location adjusted for the difference between the second viewpoint and the first viewpoint.

公开(公告)号：US11216697B1

公开(公告)日：2022-01-04

申请号：US16815787

申请日：2020-03-11

Applicant: Amazon Technologies, Inc.

Inventor： Yantao Shen ,  Yuanjun Xiong ,  Siqi Deng ,  Wei Xia ,  Shuo Yang ,  Yifan Xing ,  Wei Li ,  Stefano Soatto

IPC: G06K9/62 ,  G06K9/00 ,  G06N20/00 ,  G06F16/538

Abstract: Techniques for building a backward compatible and backfill-free image search system are described. According to some embodiments, a backwards compatible training system trains a new embedding model to be backward compatible with the face embeddings (e.g., floating-point vectors) generated by a previous embedding model. In one embodiment, backwards compatible training uses a classifier of the previous embedding model as a form of constraint in the training of the new embedding model.

公开(公告)号：US10796476B1

公开(公告)日：2020-10-06

申请号：US16119514

申请日：2018-08-31

Applicant: Amazon Technologies, Inc.

Inventor： Yifan Xing ,  Paulo Mendonca ,  Rahul Tewari

IPC: G06T15/08 ,  G06T15/04 ,  G06T17/20

Abstract: Techniques for improving a 2D to 3D image reconstruction network machine learning model are described. In some instances, this includes performing at least two transformations of a 3D model to generate at least two rotated 3D models, the at least two transformations to rotate the 3D model about an axis away from a viewing direction of the single 2D image; rendering the at least two rotated 3D models as rendered 2D images; and retraining a 2D to 3D image reconstruction network machine learning model using corresponding pairs of rotated 3D models and rendered 2D images.