arXiv (All)
open access
HDR Video Generation via Latent Alignment with Logarithmic Encoding
High dynamic range (HDR) imagery offers a rich and faithful representation of scene radiance, but remains challenging for generative models due to its mismatch with the bounded, perceptually compressed data on which these models are trained. A natural solution is to learn new representations for HDR
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
- SceneAE: Scene Generation and Reconstruction in Queryable 3D-Anchored Latent Space#1354396
- VGGA: Geometry-Grounded Autoencoder for Video Generation#1327794
- AnyView: Synthesizing Any Novel View in Dynamic Scenes#999721
- LightVAE: Towards Compact and Efficient Video Autoencoders#1325622
- The Past Frames the Future: Memory for Autoregressive Video Generation#1081341
Record · ID 1232712
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