arXiv (All)
open access
CineScale: Tuning-Free High-Resolution Video Generation
Video diffusion models have achieved remarkable progress in recent years, yet generating high-resolution videos remain a fundamental challenge. Most video generators are trained at limited spatial resolutions due to the scarcity of high-resolution 4K video data and the prohibitive computational cost
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- EpaCache: Error-Propagation-Aware Caching for Accelerating Diffusion-Based Visual Generation#794073
- EpaCache: Error-Propagation-Aware Caching for Accelerating Diffusion-Based Visual Generation#790054
- Where Compute Matters: Heterogeneous Attention for Efficient Video Diffusion#1105608
- Paris 2.0: A Decentralized Diffusion Model for Video Generation#224504
- FrescoDiffusion: 4K Image-to-Video with Prior-Regularized Tiled Diffusion#614958
Record · ID 1012049
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive