Kossar Pourahmadi Meibodi — accepted AI-conference papers

2024

CompGS: Smaller and Faster Gaussian Splatting with Vector Quantization

K L Navaneet*, Kossar Pourahmadi Meibodi, Soroush Abbasi Koohpayegani, Hamed Pirsiavash

ECCV 2024poster

"3D Gaussian Splatting (3DGS) is a new method for modeling and rendering 3D radiance fields that achieves much faster learning and rendering time compared to SOTA NeRF methods. However, it comes with a drawback in the much larger storage demand compared to NeRF methods since it needs to store the pa…

Cited by 28 Source ↗PDF ↗code ↗Scholar ↗

2023

PRANC: Pseudo RAndom Networks for Compacting Deep Models

Parsa Nooralinejad, Ali Abbasi, Soroush Abbasi Koohpayegani, Kossar Pourahmadi Meibodi, Rana Muhammad Shahroz Khan, Soheil Kolouri +1

ICCV 2023poster

We demonstrate that a deep model can be reparametrized as a linear combination of several randomly initialized and frozen deep models in the weight space. During training, we seek local minima that reside within the subspace spanned by these random models (i.e., `basis' networks). Our framework, PRA…

Cited by 12 PDF ↗code ↗Scholar ↗