公开(公告)号：US20250166288A1

公开(公告)日：2025-05-22

申请号：US18513105

申请日：2023-11-17

Applicant: Nvidia Corporation

Inventor： Or Perel ,  Maria Shugrina ,  Yoni Kasten ,  Or Litany ,  Gal Chechik ,  Sanja Fidler

IPC: G06T15/08 ,  G06T15/20

Abstract: Systems and methods of the present disclosure include providing higher levels of detail (LODs) for generated three-dimensional (3D) models, such as those represented by neural radiance fields (NeRFs). A 3D model may be presented to a user in which the user may request additional LODs, such as to zoom into the image or to receive information about features within the image. A request to generate finer levels of detail may include using one or more diffusion models to generate images at higher resolutions and/or to hallucinate finer details based on information extracted from the original image or text prompts. Newly generated images may then be added to a set of images associated with the 3D models to enable later model generation to have finer details.

公开(公告)号：US20240249458A1

公开(公告)日：2024-07-25

申请号：US18364982

申请日：2023-08-03

Applicant: NVIDIA Corporation

Inventor： Chen Tessler ,  Gal Chechik ,  Yoni Kasten ,  Shie Mannor ,  Jason Peng

IPC: G06T13/40 ,  G06N3/08 ,  G06T13/80

CPC classification number: G06T13/40 ,  G06N3/08 ,  G06T13/80

Abstract: A conditional adversarial latent model (CALM) process can be used to generate reference motions from a set of original reference movements to create a library of new movements for an agent. The agent can be a virtual representation various types of characters, animals, or objects. The CALM process can receive a set of reference movements and a requested movement. An encoder can be used to map the requested movement onto a latent space. A low-level policy can be employed to produce a series of latent space joint movements for the agent. A conditional discriminator can be used to provide feedback to the low-level policy to produce stationary distributions over the states of the agent. A high-level policy can be employed to provide a macro movement control over the low-level policy movements, such as providing direction in the environment. The high-level policy can utilize a reward or a finite-state machine function.