About InterDigital
InterDigital is a global research and development company focused primarily on wireless, video, artificial intelligence (“AI”), and related technologies. We design and develop foundational technologies that enable connected, immersive experiences in a broad range of communications and entertainment products and services. We license our innovations worldwide to companies providing such products and services, including makers of wireless communications devices, consumer electronics, IoT devices, cars and other motor vehicles, and providers of cloud-based services such as video streaming. As a leader in wireless technology, our engineers have designed and developed a wide range of innovations that are used in wireless products and networks, from the earliest digital cellular systems to 5G and today’s most advanced Wi-Fi technologies. We are also a leader in video processing and video encoding/decoding technology, with a significant AI research effort that intersects with both wireless and video technologies.
Founded in 1972, InterDigital is listed on Nasdaq.
InterDigital is a registered trademark of InterDigital, Inc.
For more information, visit: www.interdigital.com .
Summary
3D Gaussian Splatting (3DGS) is an emerging 3D scene representation in which a scene is modeled as a collection of anisotropic Gaussian primitives characterized by attributes such as position, scale, orientation, opacity, and appearance. Due to its high rendering quality and real-time performance, 3DGS has recently attracted significant interest for immersive media applications.
The Region Adaptive Hierarchical Transform (RAHT) is a hierarchical attribute transform widely used in point cloud compression standards to compact signal energy prior to entropy coding. However, RAHT was originally designed for voxelized point clouds and does not fully exploit the rich structure and correlations present in Gaussian splat representations. This internship aims to investigate novel attribute transform techniques that exploit correlations between these attributes and neighboring Gaussians. The work will explore a range of approaches, including analytical, graph-based, predictive, and potentially learning-based transforms, adapted to the characteristics of Gaussian splat representations. The objective is to achieve improved energy compaction and compression efficiency compared to RAHT while maintaining practical encoding and decoding complexity.
You will be working in the 3D Native Codec team, in the New Media Codecs Group of the Video Lab.
Responsibilities
In collaboration with the InterDigital research team, the candidate will be expected to:
Analyze existing technologies and identify core challenges related to 3D Gaussian Splat compression.
Contribute to the design and development of software solutions addressing these challenges Perform rigorous testing and validation, including simulation-based evaluations, to ensure functional correctness and performance in line with established protocols.
Implement, test, and validate the proposed components and algorithms.
Communicate technical outcomes effectively, contributing to documentation, internal reports, and potentially to publications or intellectual property filings.
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.
Keywords
Gaussian splatting, attribute compression, transform coding, graph transforms, energy compaction, entropy coding, machine learning.
Expected Outcomes
Software modules: C++ functions, python scripts
Standardization contributions
Patents
Location
Rennes, France
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