activity
20242026
collaborators

9 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

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

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.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.CV2024

EVOS: Efficient Implicit Neural Training via EVOlutionary Selector

Weixiang Zhang, Shuzhao Xie, Chengwei Ren +5

We propose EVOlutionary Selector (EVOS), an efficient training paradigm for accelerating Implicit Neural Representation (INR). Unlike conventional INR training that feeds all sampl…

cs.CV2024

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.DC2024

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…

cs.CV2024

MesonGS: Post-training Compression of 3D Gaussians via Efficient Attribute Transformation

Shuzhao Xie, Weixiang Zhang, Chen Tang +4

3D Gaussian Splatting demonstrates excellent quality and speed in novel view synthesis. Nevertheless, the huge file size of the 3D Gaussians presents challenges for transmission an…

cs.CV2024

Expansive Supervision for Neural Radiance Field

Weixiang Zhang, Shuzhao Xie, Shijia Ge +3

Neural Radiance Field (NeRF) has achieved remarkable success in creating immersive media representations through its exceptional reconstruction capabilities. However, the computati…