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Asking a Multimodal LLM Whether Someone Fell: Zero-Shot Screening of Low-Resolution Thermal Video in a Laboratory and an Occupied Home

Paper recorded by Signals 4 on 2026-10-21 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-21 on arXiv · recorded by Signals 4 on 2026-10-22

Category: cs.CV · 计算机视觉 · first seen 2026-10-22

Abstract

Thermal cameras can watch over older people living alone without capturing faces, and multimodal large language models (LLMs) can judge a short video without task-specific training. We evaluate a production multimodal LLM, Gemini 3.8 Flash at temperature 0, as the decision stage of an event-triggered fall screener, used exactly as a deployed prototype uses it: one request per short thermal clip, w

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#204 most recent of 756 cs.CV papers we have recorded · ↑ newer: CausalAlign: Causal Alignment of Video Generation Models for Consisten · ↓ older: ViBMR: A Large-Scale Multi-Sequence Brain MRI Dataset and Comprehensiv
Cite this page: Asking a Multimodal LLM Whether Someone Fell: Zero-Shot Screening of Low-Resolution Thermal Video in a Laboratory and an Occupied Home: the #204 most recent of 756 cs.CV papers we have recorded (as of 2026-10-21). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/asking-a-multimodal-llm-whether-someone-fell-zero-shot-screening-of-low-resoluti.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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