5 papers
Pocket-SLAM: Rendering-Area-Aware Pruning for Memory-Efficient 3DGS-SLAM
Leshu Li, Jie Peng, Yang Zhao
3D Gaussian Splatting (3DGS) has garnered significant attention in Simultaneous Localization and Mapping (SLAM) due to its advances in capturing fine-grained geometry features and…
LASER: Loss-Aware Singular-value Decomposition and Rank Allocation for Efficient Low-Precision Vision-Language Models
Haiyu Wang, Yutong Wang, Leshu Li +2
Vision-language models (VLMs) deliver strong multimodal reasoning capabilities, but their large computational cost and high parameter counts make deployment challenging on resource…
DSD: A Distributed Speculative Decoding Solution for Edge-Cloud Agile Large Model Serving
Fengze Yu, Leshu Li, Brad McDanel +1
Large language model (LLM) inference often suffers from high decoding latency and limited scalability across heterogeneous edge-cloud environments. Existing speculative decoding (S…
RTGS: Real-Time 3D Gaussian Splatting SLAM via Multi-Level Redundancy Reduction
Leshu Li, Jiayin Qin, Jie Peng +8
3D Gaussian Splatting (3DGS) based Simultaneous Localization and Mapping (SLAM) systems can largely benefit from 3DGS's state-of-the-art rendering efficiency and accuracy, but have…
Gaussian Blending Unit: An Edge GPU Plug-in for Real-Time Gaussian-Based Rendering in AR/VR
Zhifan Ye, Yonggan Fu, Jingqun Zhang +8
The rapidly advancing field of Augmented and Virtual Reality (AR/VR) demands real-time, photorealistic rendering on resource-constrained platforms. 3D Gaussian Splatting, deliverin…