Autonomous driving has attracted interest for interpretable action decision models that mimic human cognition. Existing interpretable autonomous driving models explore static human explanations, which ignore the implicit visual semantics that are not explicitly annotated or even consistent across annotators.
Autonomous driving has attracted interest for interpretable action decision models that mimic human cognition. Existing interpretable autonomous driving models ...
Oct 23, 2022 · In this paper, we propose a novel Interpretable Action decision making (InAction) model to provide an enriched explanation from both explicit human annotation ...
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InAction: Interpretable Action Decision Making for Autonomous Driving
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A novel Interpretable Action decision making model to provide an enriched explanation from both explicit human annotation and implicit visual semantics, ...
In this paper, we propose a novel Interpretable Action decision making (InAction) model to provide an enriched explanation from both explicit human annotation ...
Implementation of the ECCV work "InAction" for interpretable driving behavior prediction. Data Dependencies Training Evaluation
Abstract Autonomous driving attracts lots of interest in interpretable action decision models that mimic human cognition. Existing interpretable autonomous ...
InAction: Interpretable Action Decision Making for Autonomous Driving ... Authors: Taotao Jing; Haifeng Xia; Renran Tian; Haoran Ding; Xiao Luo; Joshua Domeyer ...
May 31, 2024 · We propose a decision-making model explicitly tailored for autonomous vehicles, comprising three distinct modules: needs assessment, motivation generation, and ...
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