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- Core Technology
- Based on the foundation of proprietary technologies and a core “brain” built on a deep learning platform,
SenseTime has rapidly opened up AI application in multiple vertical scenarios.
Key Technology
- 01Ultra HD Video Super-Resolution
- 022D-to-3D Video Conversion
- 03Video Summarization
- 04Video Content Structuring
- 05Short Video Labelling
- 06Video Content Review
01 / 06
Ultra HD Video Super-Resolution
Ultra HD video super-resolution converts videos to any resolution and size. Using deep learning algorithm, the technology converts transmitted low-resolution videos to high-definition videos to improve image quality for a better viewing experience.
02 / 06
2D-to-3D Video Conversion
By Imitating the 3D cognitive ability of human eyes, the technology automatically converts videos from 2D to 3D, which enhances the stereoscopic effect of the video and saves labor costs significantly. This technology can be adopted in the industries of movie, television, advertising, live streaming and so forth.
03 / 06
Video Summarization
Based on self-developed deep learning algorithm, the technology analyzes the content and style of each shot in a long video. It discovers the intrinsic relations among scenes, people and activities in each shot, and extracts key information to produce a short video summary. This technology has been applied to the television industry, mobile Internet and more.
04 / 06
Video Content Structuring
By automatically analyzing and extracting key elements from the video (such as stars and celebrities, human behaviors, fashion and apparel, scenes, logos and merchandises), the technology provides rich, structured information for efficient video content management and targeted marketing.
05 / 06
Short Video Labelling
Using industry-leading large-scale multi-label tagging algorithm, the technology automatically comprehends video content, and generates text labels to improve the performance of video search and recommendation. With the comprehensive labelling system, the technology has been successfully applied to various industries including mobile Internet, television, advertising, and more.
06 / 06
Video Content Review
Combining video classification, small sample size learning, optical character recognition(OCR), video fingerprinting and other algorithms, the technology accurately identifies inappropriate video advertisements and contents including violent and obscene materials, significantly improving the efficiency of video content review process to build a healthier Internet environment.
Technology
01 / 06
Ultra HD Video Super-Resolution
Ultra HD video super-resolution converts videos to any resolution and size. Using deep learning algorithm, the technology converts transmitted low-resolution videos to high-definition videos to improve image quality for a better viewing experience.
02 / 06
2D-to-3D Video Conversion
By Imitating the 3D cognitive ability of human eyes, the technology automatically converts videos from 2D to 3D, which enhances the stereoscopic effect of the video and saves labor costs significantly. This technology can be adopted in the industries of movie, television, advertising, live streaming and so forth.
03 / 06
Video Summarization
Based on self-developed deep learning algorithm, the technology analyzes the content and style of each shot in a long video. It discovers the intrinsic relations among scenes, people and activities in each shot, and extracts key information to produce a short video summary. This technology has been applied to the television industry, mobile Internet and more.
04 / 06
Video Content Structuring
By automatically analyzing and extracting key elements from the video (such as stars and celebrities, human behaviors, fashion and apparel, scenes, logos and merchandises), the technology provides rich, structured information for efficient video content management and targeted marketing.
05 / 06
Short Video Labelling
Using industry-leading large-scale multi-label tagging algorithm, the technology automatically comprehends video content, and generates text labels to improve the performance of video search and recommendation. With the comprehensive labelling system, the technology has been successfully applied to various industries including mobile Internet, television, advertising, and more.
06 / 06
Video Content Review
Combining video classification, small sample size learning, optical character recognition(OCR), video fingerprinting and other algorithms, the technology accurately identifies inappropriate video advertisements and contents including violent and obscene materials, significantly improving the efficiency of video content review process to build a healthier Internet environment.
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