7 citations · 9 across the 9 of their papers we have counts for
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cs.AR2026
DeGS: A Scalable 3DGS Architecture via Decoupled Workload Parsing and Reorganization
Minnan Pei, Gang Li, Zeyu Zhu +7
3D Gaussian Splatting (3DGS) has emerged as a leading technique for real-time novel view synthesis, yet existing 3DGS accelerators suffer from poor architectural scalability: incre…
cs.AR2025
GCC: A 3DGS Inference Architecture with Gaussian-Wise and Cross-Stage Conditional Processing
Minnan Pei, Gang Li, Junwen Si +6
3D Gaussian Splatting (3DGS) has emerged as a leading neural rendering technique for high-fidelity view synthesis, prompting the development of dedicated 3DGS accelerators for reso…
cs.AR2023
MEGA: A Memory-Efficient GNN Accelerator Exploiting Degree-Aware Mixed-Precision Quantization
Zeyu Zhu, Fanrong Li, Gang Li +5
Graph Neural Networks (GNNs) are becoming a promising technique in various domains due to their excellent capabilities in modeling non-Euclidean data. Although a spectrum of accele…