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most citedFasterCache: Training-Free Video Diffusion Model Acceleration with High Quality

1 citations · 3 across the 8 of their papers we have counts for

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cs.CV2026

FedHPro: Federated Hyper-Prototype Learning via Gradient Matching

Huan Wang, Jun Shen, Haoran Li +6

Federated Learning (FL) enables collaborative training of distributed clients while protecting privacy. To enhance generalization capability in FL, prototype-based FL is in the spo…

cs.CV2025

LandMarkSystem Technical Report

Zhenxiang Ma, Zhenyu Yang, Miao Tao +5

3D reconstruction is vital for applications in autonomous driving, virtual reality, augmented reality, and the metaverse. Recent advancements such as Neural Radiance Fields(NeRF) a…

cs.CV2025

GS-Cache: A GS-Cache Inference Framework for Large-scale Gaussian Splatting Models

Miao Tao, Yuanzhen Zhou, Haoran Xu +10

Rendering large-scale 3D Gaussian Splatting (3DGS) model faces significant challenges in achieving real-time, high-fidelity performance on consumer-grade devices. Fully realizing t…

cs.CV20251 cited

Vchitect-2.0: Parallel Transformer for Scaling Up Video Diffusion Models

Weichen Fan, Chenyang Si, Junhao Song +16

We present Vchitect-2.0, a parallel transformer architecture designed to scale up video diffusion models for large-scale text-to-video generation. The overall Vchitect-2.0 system h…

cs.CV20241 cited

FasterCache: Training-Free Video Diffusion Model Acceleration with High Quality

Zhengyao Lv, Chenyang Si, Junhao Song +4

In this paper, we present \textbf{\textit{FasterCache}}, a novel training-free strategy designed to accelerate the inference of video diffusion models with high-quality generation.…