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 a recent 3D scene representation in which a scene is modeled as a collection of Gaussian primitives characterized by attributes such as position, scale, orientation, opacity, and appearance. It has emerged as a promising representation for high-quality, real-time rendering of immersive visual content.
Compression of 3DGS models typically introduces distortions due to the quantization and coding of geometry and Gaussian attributes. Recent studies suggest that a limited amount of retraining after compression can partially recover rendering quality while preserving the compressed bitstream.
The objective of this internship is to investigate lightweight fine-tuning techniques integrated into the compression workflow. Starting from a compressed 3DGS representation, the intern will explore how a small subset of parameters can be adapted to compensate for compression artifacts while maintaining low computational complexity. Candidate approaches include selective optimization of attributes, as well as cluster-level or hierarchical fine-tuning strategies.
The proposed methods will be evaluated in terms of rate-distortion performance, rendering quality, retraining complexity, and encoding time. The goal is to determine whether compression-aware fine-tuning can provide significant coding gains compared to conventional compression pipelines without requiring costly model retraining.
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
3D Gaussian Splatting, compression, model fine-tuning, rate-distortion optimization, neural rendering,…