arXiv (All)
open access
PAGER: Partial-to-global Alignment via Geometric and Relational Distillation
Pretrained 3D encoders are typically developed on globally reconstructed scenes expressed in a consistent world coordinate frame, whereas embodied systems must reason from partial, viewpoint-dependent observations in camera coordinates. We show that this shift from globally learned 3D feature spaces
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
- Anchor3R: Streaming 3D Reconstruction with Transient Anchors for Long-Horizon Visual Mapping#1084235
- ReRef-3D: A Benchmark for Spatial Referring Expression-Guided 3D Scene Rearrangement#617685
- ReRef-3D: A Benchmark for Spatial Referring Expression-Guided 3D Scene Rearrangement#617185
- VGGT-Align: Bridging Local Reconstruction and Global Consistency for Long-Sequence 3D Reconstruction#615238
- VGGT-Align: Bridging Local Reconstruction and Global Consistency for Long-Sequence 3D Reconstruction#614271
Record · ID 1156860
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