{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-11948309","patent":{"patent_number":"US-11948309","title":"Systems and methods for jointly training a machine-learning-based monocular optical flow, depth, and scene flow estimator","assignee":null,"inventors":[],"filing_date":"2021-09-29T00:00:00.000Z","publication_date":"2024-04-02T00:00:00.000Z","cpc_codes":["G06T","G06T","G05D","G06N","G06N","G06N","G06N","G06N","G06T","G06T","G06T","G06T","G06T","G06T","G06T","G06T"],"num_claims":17,"abstract":"Systems and methods described herein relate to jointly training a machine-learning-based monocular optical flow, depth, and scene flow estimator. One embodiment processes a pair of temporally adjacent monocular image frames using a first neural network structure to produce an optical flow estimate and to extract, from at least one image frame in the pair of temporally adjacent monocular image frames, a set of encoded image context features; triangulates the optical flow estimate to generate a depth map; extracts a set of encoded depth context features from the depth map using a depth context encoder; and combines the set of encoded image context features and the set of encoded depth context features to improve performance of a second neural network structure in estimating depth and scene flow."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Systems and methods for jointly training a machine-learning-based monocular optical flow, depth, and scene flow estimator","description":"Systems and methods described herein relate to jointly training a machine-learning-based monocular optical flow, depth, and scene flow estimator. One embodiment processes a pair of temporally adjacent","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-11948309","license":"CC-BY-4.0-like","license_terms":"AI-generated analysis on this page (summary, layman_explanation, technical_analysis, business_analysis, faqs) may be reused with attribution and a visible link back to the canonical URL above. Patent abstracts, claims, and bibliographic data are USPTO public domain.","required_link":"https://patentable.app/patents/US-11948309","citation_suggestion":"Patentable. \"Systems and methods for jointly training a machine-learning-based monocular optical flow, depth, and scene flow estimator\" (US-11948309). https://patentable.app/patents/US-11948309","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-11948309","json":"https://patentable.app/api/llm-context/US-11948309","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-31T06:07:17.925Z"}