3 offres trouvées

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...

Summary The InterDigital Immersive Video Lab is focused on advancing avatar-based communication. In this context, accurate and detailed human 3D data is essential for reliably estimating features such as facial expressions, body posture, skin texture, lighting conditions, background segmentation, hair segmentation, and more. InterDigital has developed a proprietary framework for generating synthetic 3D facial image datasets. The next step is to enhance this framework to support the creation of 4D video sequences featuring full-body characters. This internship will contribute to the development and refinement of this extended capability. Responsibilities The goal of the internship will be to: Study state of the art on face & body analysis models and synthetic data generation Update the framework to full body with body animation Upgrade the framework to output video sequences Create and/or set up avatar elements (clothes, accessories, jewels etc.) Generate video...

Summary Research-oriented internship on multi-user Quality of Experience (QoE) for XR application, the intern will survey the state of the art, identify and formalize QoE metrics specific to multi-user XR, and propose/enhance a composite QoE metric with corresponding instrumentation. The intern will design and run controlled experiments to collect metrics across concurrent users, analyze correlations with perceived experience, and iterate on the model. The work may culminate in planning and conducting user studies in the Rennes lab. Expected outcomes: a literature review, a measurement framework/prototype, practical recommendations for QoE-aware adaptation in multi-user XR, participation in a scientific paper, and potential disclosures. Responsibilities State of the art in QoE in XR, and Multi-User scenarios Propose or refine a composite QoE metric and map each factor to measurable KPIs and thresholds Design and implement instrumentation to capture interaction signals across...