FlexGaussian: Flexible and Cost-Effective Training-Free Compression for 3D Gaussian Splatting
Year: 2025
Type: conference-paper
Abstract: 3D Gaussian Splatting has emerged as a prominent technique for representing and rendering complex 3D scenes, offering high fidelity and speed but resulting in large file sizes. Existing compression methods can reduce 3D Gaussian data size but often require costly retraining or refinement, which is memory- and compute-intensive and lacks flexibility for varying compression needs. This challenge grows as large-scale scenes become more common, increasing the demand for efficient, low-overhead compression methods - especially for resource-constrained mobile and edge devices.
Authors: Boyuan Tian, Qizhe Gao, Siran Xianyu, Xiaotong Cui, Minjia Zhang
Institution: University of Illinois Urbana-Champaign
Language: English
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Awards: G1353381076, G1453181110, G1503004319, Track 4: Advanced CI Coordination Ecosystem: Monitoring and Measurement Services, G2154383771, G2848635288, G298330452, G3562386289, Track 1: ACCESS Resource Allocations Marketplace and Platform Services (RAMPS), G4010157413, G4403015908, ACO: An Open CI Ecosystem to Advance Scientific Discovery (OpenCI), Category I: Crossing the Divide Between Today's Practice and Tomorrow's Science, Track 3: COre National Ecosystem for CyberinfrasTructure (CONECT), G5367127336, G5464919783, G6709186444, G6754955425, G8108599699, Track 2: Customized Multi-tier Assistance, Training, and Computational Help (MATCH) for End User ACCESS to CI, G8562358136, G8617358649, G8851268641, CAREER: A Framework to Power Next-Generation AI-based Scientific Models on Hardware with Massive Parallelism
OpenAlex ID: W4415540947