Grenoble, France

Anurag Arnab

USPTO Granted Patents = 2 

Average Co-Inventor Count = 6.0

ph-index = 1


Company Filing History:


Years Active: 2024-2025

where 'Filed Patents' based on already Granted Patents

2 patents (USPTO):

Title: Anurag Arnab: Innovator in Video Understanding Technologies

Introduction

Anurag Arnab is a prominent inventor based in Grenoble, France. He has made significant contributions to the field of machine learning and video understanding. With a total of 2 patents, Arnab is recognized for his innovative approaches to processing and interpreting multimedia data.

Latest Patents

Arnab's latest patents include groundbreaking systems and methods for enhancing video understanding. One of his patents focuses on pre-training a model using unlabeled videos. This method involves receiving unlabeled multimedia data and generating captions through a machine learning model. The process includes inputting a subset of video frames and a first utterance, predicting a second utterance, and updating the model's parameters based on a loss function.

Another notable patent is a computer-implemented method for classifying video data with improved accuracy. This method extracts video tokens that represent spatiotemporal information from video data. These tokens are then input into a video understanding model, which utilizes a video transformer encoder to produce classification outputs.

Career Highlights

Anurag Arnab is currently employed at Google Inc., where he continues to push the boundaries of technology in video understanding. His work has garnered attention for its potential applications in various industries, including entertainment and security.

Collaborations

Arnab collaborates with talented individuals such as Mostafa Dehghani and Georg Heigold. Their combined expertise contributes to the advancement of innovative solutions in the field of machine learning.

Conclusion

Anurag Arnab is a key figure in the realm of video understanding technologies. His patents reflect a commitment to enhancing machine learning applications, making significant strides in how we interpret multimedia data. His contributions are paving the way for future innovations in this exciting field.

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