MUMBAI, India, Sept. 12 -- Intellectual Property India has published a patent application (202517080843 A) filed by Google Llc, Mountain View, U.S.A., on Aug. 26, for 'monocular depth and optical flow estimation using diffusion models.'
Inventor(s) include Saxena, Saurabh; Norouzi, Mohammad; Fleet, David; Kar, Abhishek; Herrmann, Charles; Hur, Junhwa; and Sun, Deqing.
The application for the patent was published on Sept. 12, under issue no. 37/2025.
According to the abstract released by the Intellectual Property India: "Improved methods are provided for generating, via a noise-diffusion iterative process, depth maps or optical flow maps from input images. Also provided are improved methods for training the machine learning model(s) employed in the iterative process and for augmenting die set of training data used to train such models. By translating the depth or optical flow map prediction process into the noise diffusion context, improved performance with respect to compute cost, training data, requirements, model size, and output quality are obtained. Additionally, the noise diffusion context allows models trained as described herein to generate maps de novo from target color images and/or to begin from initial 'guess' maps (e.g., noisy maps, maps containing holes) when generating improved output maps, natively incorporating the imperfect prior information represented by such initial maps."
The patent application was internationally filed on Jan. 26, 2024, under International application No.PCT/US2024/013078.
Disclaimer: Curated by HT Syndication.
