arXiv (All)
open access
MatchFusion: Explicit-Implicit Instance Matching for Spatio-Temporal Multimodal Autonomous Driving
Sparse instance representations provide a compact interface for spatial LiDAR-camera and temporal past-current interaction in multimodal perception and E2EAD. Effective interaction requires reliable instance correspondences despite geometric discrepancies and heterogeneous semantic representations.
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
- Retrieve-to-Localize: Bridging Large Language Models and LiDAR Geometry for Spatial Grounding#1077762
- Scene tokenization for unified perception in autonomous driving#370132
- Do LiDAR Language Models Really Understand Spatio-temporal Relationships?#1050628
- S4VY: Segment Anything in Feed-Forward 4D Visual Geometry#1132076
- Learning to Reason with Persistent Object States for Video Instance Segmentation#1130120
Record · ID 1061488
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