公开(公告)号：US20220101494A1

公开(公告)日：2022-03-31

申请号：US17039805

申请日：2020-09-30

Applicant: NVIDIA Corporation

Inventor： Morteza Mardani Korani ,  Guilin Liu ,  Aysegul Dundar ,  Shiqiu Liu ,  Andrew J. Tao ,  Bryan Christopher Catanzaro

IPC: G06T3/40 ,  G06K9/62

Abstract: Apparatuses, systems, and techniques to scale textured images using a Fourier transform in conjunction with one or more neural networks. In at least one embodiment, a neural network generates an expanded image from an input image by applying a Fourier transform to one or more feature maps generated by said neural network and up-scaling one or more resulting frequency domain feature maps before generating an expanded output image based on up-scaled feature maps.

公开(公告)号：US20220222778A1

公开(公告)日：2022-07-14

申请号：US17710643

申请日：2022-03-31

Applicant: NVIDIA Corporation

Inventor： Shiqiu Liu ,  Robert Thomas Pottorff ,  Guilin Liu ,  Karan Sapra ,  Jon Barker ,  David Tarjan ,  Pekka Janis ,  Edvard Olav Valter Fagerholm ,  Lei Yang ,  Kevin Jonathan Shih ,  Marco Salvi ,  Timo Roman ,  Andrew Tao ,  Bryan Christopher Catanzaro

IPC: G06T3/40 ,  G06T5/20 ,  G06T5/50 ,  G06T5/00

Abstract: Apparatuses, systems, and techniques are presented to generate images. In at least one embodiment, one or more neural networks are used to generate one or more images using one or more pixel weights determined based, at least in part, on one or more sub-pixel offset values.

公开(公告)号：US20190295228A1

公开(公告)日：2019-09-26

申请号：US16360895

申请日：2019-03-21

Applicant: NVIDIA Corporation

Inventor： Guilin Liu ,  Fitsum A. Reda ,  Kevin Shih ,  Ting-Chun Wang ,  Andrew Tao ,  Bryan Catanzaro

IPC: G06T5/00 ,  G06T5/20 ,  G06N3/08 ,  G06N20/10 ,  G06T3/40

Abstract: A neural network architecture is disclosed for performing image in-painting using partial convolution operations. The neural network processes an image and a corresponding mask that identifies holes in the image utilizing partial convolution operations, where the mask is used by the partial convolution operation to zero out coefficients of the convolution kernel corresponding to invalid pixel data for the holes. The mask is updated after each partial convolution operation is performed in an encoder section of the neural network. In one embodiment, the neural network is implemented using an encoder-decoder framework with skip links to forward representations of the features at different sections of the encoder to corresponding sections of the decoder.

公开(公告)号：US20230186428A1

公开(公告)日：2023-06-15

申请号：US18106348

申请日：2023-02-06

Applicant: NVIDIA Corporation

Inventor： Guilin Liu ,  Andrew Tao ,  Bryan Christopher Catanzaro ,  Ting-Chun Wang ,  Zhiding Yu ,  Shiqiu Liu ,  Fitsum Reda ,  Karan Sapra ,  Brandon Rowlett

IPC: G06T3/40 ,  G06T7/40 ,  G06N3/08 ,  G06V10/776 ,  G06V10/82 ,  G06V10/44 ,  G06V10/54

CPC classification number: G06T3/4038 ,  G06T3/4046 ,  G06T7/40 ,  G06N3/08 ,  G06V10/776 ,  G06V10/82 ,  G06V10/454 ,  G06V10/54 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: Apparatuses, systems, and techniques for texture synthesis from small input textures in images using convolutional neural networks. In at least one embodiment, one or more convolutional layers are used in conjunction with one or more transposed convolution operations to generate a large textured output image from a small input textured image while preserving global features and texture, according to various novel techniques described herein.

公开(公告)号：US20220261593A1

公开(公告)日：2022-08-18

申请号：US17177068

申请日：2021-02-16

Applicant: NVIDIA Corporation

Inventor： Zhiding Yu ,  Shiyi Lan ,  Chris Choy ,  Subhashree Radhakrishnan ,  Guilin Liu ,  Yuke Zhu ,  Anima Anandkumar

IPC: G06K9/62 ,  G06T7/11 ,  G06K9/00 ,  G06N3/04 ,  G06N3/08

Abstract: Apparatuses, systems, and techniques to train one or more neural networks. In at least one embodiment, one or more neural networks are trained to perform segmentation tasks based at least in part on training data comprising bounding box annotations.

公开(公告)号：US20200160593A1

公开(公告)日：2020-05-21

申请号：US16685538

申请日：2019-11-15

Applicant: NVIDIA Corporation

Inventor： Jinwei Gu ,  Kihwan Kim ,  Jan Kautz ,  Guilin Liu ,  Soumyadip Sengupta

IPC: G06T15/50 ,  G06T9/00 ,  G06N3/04 ,  G06N3/08

Abstract: Inverse rendering estimates physical scene attributes (e.g., reflectance, geometry, and lighting) from image(s) and is used for gaming, virtual reality, augmented reality, and robotics. An inverse rendering network (IRN) receives a single input image of a 3D scene and generates the physical scene attributes for the image. The IRN is trained by using the estimated physical scene attributes generated by the IRN to reproduce the input image and updating parameters of the IRN to reduce differences between the reproduced input image and the input image. A direct renderer and a residual appearance renderer (RAR) reproduce the input image. The RAR predicts a residual image representing complex appearance effects of the real (not synthetic) image based on features extracted from the image and the reflectance and geometry properties. The residual image represents near-field illumination, cast shadows, inter-reflections, and realistic shading that are not provided by the direct renderer.