単一ショットで歩行者検出と行動予測を同時に行うマルチタスク手法
Single Shot Multitask Pedestrian Detection and Behavior Prediction
カメラ画像から歩行者の検出と意図予測を1回の推論で同時に行う時空間マルチタスクアーキテクチャを提案し、組み込み向けに低遅延・高精度を実現した。
著者: Prateek Agrawal, Pratik Prabhanjan Brahma
分類: cs.AI, cs.CV, cs.RO
原文アブストラクト
Detecting and predicting the behavior of pedestrians is extremely crucial for self-driving vehicles to plan and interact with them safely. Although there have been several research works in this area, it is important to have fast and memory efficient models such that it can operate in embedded hardware in these autonomous machines. In this work, we propose a novel architecture using spatial-temporal multi-tasking to do camera based pedestrian detection and intention prediction. Our approach significantly reduces the latency by being able to detect and predict all pedestrians' intention in a single shot manner while also being able to attain better accuracy by sharing features with relevant object level information and interactions.