collaborators

8 papers

cs.CV2026

MesonGS++: Post-training Compression of 3D Gaussian Splatting with Hyperparameter Searching

Shuzhao Xie, Junchen Ge, Weixiang Zhang +10

3D Gaussian Splatting (3DGS) achieves high-quality novel view synthesis with real-time rendering, but its storage cost remains prohibitive for practical deployment. Existing post-t…

cs.CV2026

VVS: Accelerating Speculative Decoding for Visual Autoregressive Generation via Partial Verification Skipping

Haotian Dong, Ye Li, Rongwei Lu +3

Visual autoregressive (AR) generation models have demonstrated strong potential for image generation, yet their next-token-prediction paradigm introduces considerable inference lat…

cs.CV2026

Tail-Aware Post-Training Quantization for 3D Geometry Models

Sicheng Pan, Chen Tang, Shuzhao Xie +6

The burgeoning complexity and scale of 3D geometry models pose significant challenges for deployment on resource-constrained platforms. While Post-Training Quantization (PTQ) enabl…

cs.CV2025

SizeGS: Size-aware Compression of 3D Gaussian Splatting via Mixed Integer Programming

Shuzhao Xie, Jiahang Liu, Weixiang Zhang +7

Recent advances in 3D Gaussian Splatting (3DGS) have greatly improved 3D reconstruction. However, its substantial data size poses a significant challenge for transmission and stora…

cs.CV2025

Accelerating Parallel Diffusion Model Serving with Residual Compression

Jiajun Luo, Yicheng Xiao, Jianru Xu +5

Diffusion models produce realistic images and videos but require substantial computational resources, necessitating multi-accelerator parallelism for real-time deployment. However,…

cs.DC2025

Staleness-Centric Optimizations for Parallel Diffusion MoE Inference

Jiajun Luo, Lizhuo Luo, Jianru Xu +4

Mixture-of-Experts-based (MoE-based) diffusion models demonstrate remarkable scalability in high-fidelity image generation, yet their reliance on expert parallelism introduces crit…