Meta Platforms had 73 patents in artificial intelligence during Q1 2024. Meta Platforms Inc has filed patents for various technologies including free-viewpoint rendering of dynamic scenes using neural radiance fields, training artificial neural networks using cluster analysis, generating altered speech signals based on target emotions, and suspending/resuming tasks on assistant systems. These patents showcase advancements in computer vision, artificial intelligence, speech processing, and task management technologies. GlobalData’s report on Meta Platforms gives a 360-degree view of the company including its patenting strategy. Buy the report here.
Meta Platforms grant share with artificial intelligence as a theme is 38% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Animatable neural radiance fields from monocular rgb-d inputs (Patent ID: US20240104828A1)
The patent filed by Meta Platforms Inc. describes a method and system for generating a free-viewpoint rendering of a dynamic scene using an improved neural radiance fields (NeRF) based model. The method involves accessing image frames and depth information, generating latent representations based on point clouds and temporal relationships, and training the NeRF model for rendering. The system utilizes camera parameters and key frames to complete missing information and allows for rendering from novel viewpoints, even for unseen poses of objects in the scene.
The method further includes training the NeRF model by generating color and density values for rendering, comparing with ground-truth images, and updating the model based on the loss. Additionally, the system can handle human subjects in motion, capturing appearance details like facial and body characteristics. The method also involves user input for selecting desired novel viewpoints and utilizes neural networks for generating latent representations. The system can be implemented using processors and computer-readable storage media to access, generate, and train the NeRF model for free-viewpoint rendering of dynamic scenes.
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