5 papers
Self-Geometry: GT-Free and Plug-and-Play Test-Time Adaptation for Geometrically Consistent 3D Vision Foundation Models
Seokhyun Youn, Dahyeon Kye, Sung-Ho Bae +1
Recent Vision Foundation Models (VFMs) predict depth, camera pose, and pointmap in a single forward pass without per-scene optimization, achieving strong generalization. However, e…
I-INR: Iterative Implicit Neural Representations
Ali Haider, Muhammad Salman Ali, Maryam Qamar +5
Implicit Neural Representations (INRs) have revolutionized signal processing and computer vision by modeling signals as continuous, differentiable functions parameterized by neural…
SUCCESS-GS: Survey of Compactness and Compression for Efficient Static and Dynamic Gaussian Splatting
Seokhyun Youn, Soohyun Lee, Geonho Kim +3
3D Gaussian Splatting (3DGS) has emerged as a powerful explicit representation enabling real-time, high-fidelity 3D reconstruction and novel view synthesis. However, its practical…
Compression in 3D Gaussian Splatting: A Survey of Methods, Trends, and Future Directions
Muhammad Salman Ali, Chaoning Zhang, Marco Cagnazzo +3
3D Gaussian Splatting (3DGS) has recently emerged as a pioneering approach in explicit scene rendering and computer graphics. Unlike traditional neural radiance field (NeRF) method…
ELMGS: Enhancing memory and computation scaLability through coMpression for 3D Gaussian Splatting
Muhammad Salman Ali, Sung-Ho Bae, Enzo Tartaglione
3D models have recently been popularized by the potentiality of end-to-end training offered first by Neural Radiance Fields and most recently by 3D Gaussian Splatting models. The l…