InterDigital
Summary
In this internship at the London AI Video Lab, the objective is to study fixed-point arithmetic solutions for ensuring bit-exact video compression in AI-based video codecs. Current AI-based video compression models outperform conventional codecs, like HEVC, VVC and AV1. However, AI-based video compression models are trained using floating-point arithmetic. Unfortunately, floating point arithmetic is insufficient to ensure bit-exact execution. Bit-exact execution is needed to ensure encoded bitstreams are universally decodable across any device. Fixed-point arithmetic is a potential solution to this problem. The goal of the internship is to determine a fixed-point arithmetic setup capable of ensuring bit-exactness while maintaining model performance.
This work will be seen as one step forward toward the deployment of end-to-end trained AI-based video compression models.
The goal will be to study various fixed-point arithmetic setups for layers and components of AI-based...
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Qualifications
List minimum required qualifications, preferred skills, abilities, experience, and education
MSc in Computer Science, Machine Learning, Mathematics, Physics or a related field
Fluency in C++ and Python, video processing, computer vision, PyTorch
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| Durée (Mois): |
6
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