arXiv (All)
open access
Dyn-3D: Unveiling and Resolving Ego-Motion Ambiguity in Vision-Language Models
As Vision-Language Models (VLMs) tackle dynamic 3D spatial reasoning, ego-motion perception becomes essential to resolve monocular scale ambiguity. However, current models often overfit to smooth trajectory priors rather than genuinely understanding physical motion. Consequently, their spatial reaso
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
- DeltaWAM: Change-Centric Visual Foresight via Delta Tokens for an Efficient World-Action Model#1117889
- Open-Vocabulary BEV Segmentation with 3D-Aware Geometric Constraints#303214
- Pixel-level understanding of a world in motion within a neural encoding framework#120137
- Seeing as Humans Do: Learning from Motion to Segment Anything Without Supervision#1144952
- EgoEverything: A Benchmark for Human Behavior Inspired Long Context Egocentric Video Understanding in AR Environment#2604
Record · ID 821044
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