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7 offres trouvées

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InterDigital Sur site Bretagne
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InterDigital
26 oct., 2025
STAGE, Stage
InternMulti-User Qoe H/F
InterDigital 48.1336951,-1.6190308
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...
Qualifications Enrolled in a m2 or final-year engineering program in Computer Science or related field Good foundation in real-time computer graphics architecture Hands-on experience with Unity or Unreal Engine or related software Literature review skills, ability to synthetize papers into clear technical insights Clear written and spoken English Confident presenting results to technical audiences
Durée (Mois):
6
InterDigital
26 oct., 2025
STAGE, Stage
InternView-Dependent Realistic Human Faces For Real-Time Avatar Communication H/F
InterDigital 48.1336951,-1.6190308
Summary The InterDigital Immersive Video Lab is dedicated to advancing avatar-based communication. With the fast-paced technology and research advancements in view-dependent rendering such as the work done with neural radiance fields (NeRF) and more recently Gaussian splats, one can witness the improvement in visual quality of static and dynamic scenes including avatar models. This internship will contribute to the development of view-dependent realistic human faces. Responsibilities Develop a real-time animation platform based on facial animation using 3DGS technology and MPEG ARF standards Propose representation formats for 3DGS Avatar Representation using both traditional and advanced techniques e.g., mesh based, AI based and 3DGS based Keywords: Avatar, Animation, Neural Networks, 3D Gaussians Splats Expected Outcomes: Patents, Publications and Demos
Qualifications Master - 3D computer vision, computer graphics, 3D modeling, rendering, Maya/Houdini/Blender
Durée (Mois):
6
InterDigital
26 oct., 2025
STAGE, Stage
InternDeep-Reference Frame For Video Coding H/F
InterDigital 48.1336951,-1.6190308
Summary Short paragraph about the role, accountabilities, and any business until or department specific information The goal of the project is to explore video coding improvement using an additional reference picture generated with a deep neural network (Deep Learning) also known as Deep Reference Frame (DRF). Since a large part of network traffic consists of video content, image compression has become a key challenge to reduce the volume of transmitted data. The project context is VVC video compression. VVC is the latest video compression standard developed by the ISO/IEC and ITU-T standardization bodies. Recently, it has been proposed to use deep learning based image generation (DRF: Deep Reference Frame) to predict certain frames and reduce the bitrate of transmitted video content. Indeed, temporal frame interpolation using Deep Learning techniques is advancing rapidly. Responsibilities List primary responsibilities State-of-art of DRF and analysis of a particular...
Qualifications List minimum required qualifications, preferred skills, abilities, experience, and education Required qualifications: knowledge in machine learning, good knowledge of python Preferred skills: knowledge of C++ programming, deep learning framework (Pytorch) or scripts writing would be appreciated, Other: Research background in signal processing and image processing
Durée (Mois):
6
InterDigital
26 oct., 2025
STAGE, Stage
InternFull Body 4D Synthetic Datasets H/F
InterDigital 48.1336951,-1.6190308
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...
Qualifications Master - computer graphics, 3D modeling, rendering, Maya/Houdini/Blender
Durée (Mois):
6
InterDigital
26 oct., 2025
STAGE, Stage
InternEfficient Encoding Of 3D Gaussian Splat Representations H/F
InterDigital 48.1336951,-1.6190308
Summary In recent years, a variety of volumetric representations have been developed to support New View Generation (NVG)-the process of synthesizing novel perspectives of a scene from a limited set of captured views. Among these, 3D Gaussian Splatting (3DGS) has emerged as a leading technique, offering high-quality rendering of volumetric data with impressive realism and efficiency, marking a significant shift in how 3D scenes are represented. 3DGS models scenes as dense collections of 3D ellipsoidal primitives, each defined by a Gaussian function that supports anisotropic scaling, rotation, and stretching. These primitives also encode view-dependent color and opacity, allowing for nuanced and realistic rendering from multiple angles. However, this rendering quality comes at the cost of a large data footprint, which has sparked growing interest in efficient compression techniques, particularly within MPEG, where standardization efforts are actively progressing. In this context,...
Qualifications Master's student in Computer Engineering, Computer Science, Software Engineering, or a closely related discipline. Strong proficiency in C/C++ and Python is required. Familiarity with one or more of the following areas is a plus: 3D geometry, compression, computer vision, or computer graphics. Fluent in English, with excellent written and verbal communication skills. Demonstrates strong collaboration abilities and a team-oriented mindset.
Durée (Mois):
6
InterDigital
25 oct., 2025
STAGE, Stage
InternDistributed Inference For Multi-Modal Large Language Models Mllms With Agentic ai Orchestration H/F
InterDigital 48.1336951,-1.6190308
Summary Multi-Modal Large Language Models (MLLMs) are increasingly capable of processing and reasoning over diverse input modalities such as text, images, audio, and video. However, running such models in real-time or resource-constrained environments poses significant challenges in terms of bandwidth and compute requirements. Distributing the processing of models between client and server (a "distributed computing" approach) is a promising solution. While traditional distributed inferencing has been applied successfully to DNN models, extending this paradigm to MLLMs is a novel and impactful use case. This internship aims to demonstrate the feasibility of distributed MLLMs inference approach, where MLLM components are distributed across two endpoints, coordinated through an agentic orchestration. Responsibilities The internship will be involved in the following tasks: Survey the recent advances in MLLMs, Select representative models, and a representative agentic...
Qualifications Education: Master's student in Computer Science, Artificial Intelligence, Data Science, or related field. Skills: Background in AI/ML, particularly large language models. Knowledge of multi-modal systems (text, vision, speech). Proficiency in Python programming and ML frameworks (PyTorch). Ability to conduct research and prototype efficiently. Nice to have: familiarity with distributed systems, networking, bandwidth concepts, ONNX framework
Durée (Mois):
6
InterDigital
25 oct., 2025
STAGE, Stage
InternMulti-User Qoe Xr Demonstrator Development Internship H/F
InterDigital 48.1336951,-1.6190308
Summary The System for Enhanced Media Representation team (SEMR) is developing a Unity 3D based platform to demonstrate our technologies regarding Multi-Users Quality of Experience (QoE) for eXtended Reality (XR) applications and test new functionalities. eXtended Reality (XR) is a general term encapsulating augmented, mixed and virtual reality (AR, MR and VR), with a strong emphasis on immersion and interactions between virtual and real world. Multi-Users experiences provide a shared environment for each participant. They rely on network communication to synchronize data and offer inter user interactivity. Quality of Experience (QoE) refers to the subjective perception of quality for a given experience. In the context of a network based XR application, this can be influenced by interactivity level, response time, spatial stability, graphics quality, etc. Maintaining high level of QoE even during network perturbations is an active field of study. During this 6-month...
Qualifications Graduate student (M.Sc. or Ph.D.) in Computer Science, Computer Engineering, Software Engineering or related fields Interest in any of the following fields: 3D geometry, computer graphics, networking, XR, user experience (UX), interactivity Familiarity with Unity 3D and C# (shaders and graphics API knowledge is a plus) Scripting (bash, python) Versioning notion, ideally with Git Professional English proficiency (French is a plus) Good communication skills, team player Willing to learn, fail and learn some more
Durée (Mois):
6
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