arXiv (All)
open access
Detecting Phone-Induced Pedestrian Distraction via a Multimodal Fusion Transformer
The increasing reliance on mobile phones has made phone-induced pedestrian distraction increasingly prevalent. Activities such as texting, watching videos, and making phone calls have become significant contributors to traffic accidents. Reliable detection of pedestrian distraction is essential for
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
- Silent Alert: AI-Enhanced Hand Sign Recognition for Real Time Emergency via CCTV#119420
- Pedestrian localization, tracking and behavior analysis from multiple cameras#1100293
- Coordinating Speech with Touch Input and Visual Cues in Human–Robot Interaction: A Multimodal System Evaluated through Metamorphic Testing#189734
- Is Tracking really more challenging in First Person Egocentric Vision?#987455
- An information fusion framework for person localization via body pose in spectator crowds#818338
Record · ID 1049246
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