Real-world video understanding

We build advanced machine learning systems that understand video

Range of uses
Wide Range of Applications
Use cases range from human gesture recognition to security video monitoring
Custom datasets
Custom Datasets
We own some of the largest industry datasets for intelligent video analysis
Real time
Runs in Real-time
Our software extracts meaning from continuous video streams in real-time
Flexible licensing
Flexible Licensing
Licensing options range from one-off royalty to subscription models

Our mission

When humans solve intelligent tasks, they rely heavily on their common sense knowledge about the world. A detailed understanding of the physical world is however still largely missing from current applications in artificial intelligence and robotics. Our mission is to change that. We are developing new, ground-breaking technology that allows machines to perceive the world like humans.

How it works

Our technology can analyze video and extract meaning from it in real-time. We build deep learning systems using our large video datasets about common world situations and then fine-tune them to specific use cases with minimal effort.

A novel database

One of the limiting factors for advancing video understanding is the lack of large and diverse real-world video datasets. To circumvent this bottleneck, we have built a scalable crowd-acting platform and have created some of the largest industry video datasets for training deep neural networks.

A unique approach

Our deep neural networks are pre-trained on our datasets of crowd-acted videos. The datasets contain short video clips that show a wide range of physical and human actions. We then transfer the capabilities of our trained network to contribute to specific video applications.

How it works

Step 1

We pre-train deep neural networks on a foundational dataset for understanding physical actions. A large amount of annotated video data is required so that the models develop an internal representation of how objects interact in the real world.

Step 2

We transfer this intrinsic knowledge to solve problems of high complexity that rely on an understanding of these fundamental physical concepts. The data requirements are drastically lower, allowing us to solve a large variety of video use cases.

Use Cases

Our machine learning systems excel at deciphering complex human behavior in video

Gesture recognition
Gesture Recognition
Automatic detection of dynamic hand gestures for human-computer interaction
Social robotics
Personal Home Robots
Visual scene understanding for domestic robots interacting with humans
Elderly care
Elderly Fall Detection
Automatic detection of accidental falls among elderly people at home
Aggression detection
Aggression Detection
Automatic detection of aggressive behavior in public transport systems
Theft detection
Theft Detection
Automatic detection of suspicious activity like theft or shoplifting in stores
Video based ad suggestions
Video-based Ad Suggestions
Media system that automatically places ads based on the video's content
Textual video search
Textual Video Search
Media system that allows users to search and discover video content
Video content moderation
Video Content Moderation
Media system that automatically detects and removes offensive video material

Our Data Factory

We are crowdsourcing large-scale video datasets that explain the world in videos

Data factory

Our Core Datasets

Objects
General Visual Knowledge
Our core dataset is used to teach machines common sense and basic physical concepts
Human actions
Human Actions
Our scene understanding dataset is used to detect human behavior and complex actions in context
Gestures
Hand Gestures
The world's largest video-based dataset for reading dynamic hand gestures

About Us

We are a technical team that is re-defining how machines understand our world

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Dr. Christian Thurau
Chief Biz Dev Officer & Co-Founder
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Dr. Roland Memisevic, PhD
Chief Scientist & Co-Founder
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Dr. Florian Hoppe
Chief Operating Officer & Co-Founder
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Dr. Ingo Bax
Chief Technology Officer & Co-Founder
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Valentin Haenel
VP of Engineering
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Susanne Westphal
A.I. Engineer
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Moritz Müller-Freitag
Chief Product Officer
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Joanna Materzynska
Junior A.I. Engineer
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Raghav Goyal
A.I. Engineer
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Dr. Heuna Kim
A.I. Researcher
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Manuela Hartmann
Executive Assistant & Office Manager
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Fadi Abu-Gharbieh
Data Engineer
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Eren Gölge
A.I. Engineer
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Héctor Marroquin
Crowdsourcing Supporter
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Farzaneh Mahdisoltani
Research Intern
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Waseem Gharbieh
Deep Learning Researcher
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Guillaume Berger
Research Intern
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Till Breuer
A.I. Engineer
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Advisors

Yoshua bengio
Yoshua Bengio
MONTREAL INSTITUTE FOR LEARNING ALGORITHMS
Nathan benaich
Nathan Benaich
Peter yianilos
Peter N. Yianilos
CEO EDGESTREAM PARTNERS

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