arXiv (All)
open access
SemanticSlider3D: Training-Free Continuous Semantic Editing for 3D Objects
Fine-grained control over continuous semantic attributes of 3D objects is essential for 3D content creation, but is not well supported by conventional 3D modeling workflows or prompt-based interaction with existing generative AI tools. While slider-based methods have proven effective for fine-graine
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
- SemanticSlider3D: Training-Free Continuous Semantic Editing for 3D Objects#788806
- RenderFormer-V2: Neural Rendering with Heterogeneous Scene Primitives#972784
- Generative AI and Extended Reality in Collaborative Architectural Design Education: An Exploratory Studio Study#1071278
- HMB-GAN: Hybrid Multi-Bézier GAN for Vector Shape Synthesis#1035126
- Potential Role and Challenges of ChatGPT and Similar Generative Artificial Intelligence in Architectural Engineering#478151
Record · ID 792810
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