arXiv (All)
open access
Channel Match: Calibrating Shape Latents for Few-Step 3D Generation
Recent native 3D generators achieve high-quality asset creation by modeling structured 3D latents with flow-based transformers, but their high-resolution generation remains computationally expensive due to costly iterative sampling. In this work, we introduce a few-step distillation framework for na
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
- DistScene: Object-to-Scene Distillation for 3D Scene Generation#1216042
- uFlowCSP: Crystal Structure Prediction using Mean flow generative models#996619
- Guiding Image-to-3D Generation with Test-Time Partial Observations#997402
- Native3D: End-to-End 3D Scene Generation via Unified Mesh-Texture Modeling and Semantic Alignment#266232
- CADrawer: Autoregressive CAD Generation from 3D Sketches#195735
Record · ID 1326571
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