Proof pending. This topic has not reached the minimum paper threshold yet.
Text-driven 3D scene editing has attracted considerable interest due to its convenience and user-friendliness. However, methods that rely on implicit 3D representations, such as Neural Radiance Fields...
Leveraging the priors of 2D diffusion models for 3D editing has emerged as a promising paradigm. However, maintaining multi-view consistency in edited results remains challenging, and the extreme scar...
Most instruction-driven 3D editing methods rely on 2D models to guide the explicit and iterative optimization of 3D representations. This paradigm, however, suffers from two primary drawbacks. First, ...
Indirect editing methods for 3D Gaussian Splatting (3DGS) have recently witnessed significant advancements. These approaches operate by first applying edits in the rendered 2D space and subsequently p...
Freshness
Canonical route: /topics
Agent Handoff
Canonical ID 3d-editing | Route /topic/3d-editing
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/topic/3d-editingMCP example
{
"tool": "search_papers",
"arguments": {
"query": "3D Editing",
"cluster": "3D Editing"
}
}source_context
{
"surface": "topic",
"mode": "topic",
"query": "3D Editing",
"normalized_query": "3d-editing",
"route": "/topic/3d-editing",
"paper_ref": null,
"topic_slug": "3d-editing",
"benchmark_ref": null,
"dataset_ref": null
}Use This Via API or MCP
Topic pages bundle paper counts, viability trends, author concentration, and top questions into one canonical surface your agents can reference before they open Signal Canvas or create a workspace.