Recurrent 3D attentional networks for end-to-end active object recognition
Sign Up to like & getrecommendations! Published in 2019 at "Computational Visual Media"
DOI: 10.1007/s41095-019-0135-2
Abstract: Active vision is inherently attention-driven: an agent actively selects views to attend in order to rapidly perform a vision task while improving its internal representation of the scene being observed. Inspired by the recent success… read more here.
Keywords: active object; recurrent attentional; object recognition; recognition ... See more keywords
Observations Temporal Permutation-Based Self-Supervised Reinforcement Learning for UAV Active Object Detection
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DOI: 10.1109/tgrs.2025.3621519
Abstract: In passive ground target detection using unmanned aerial vehicles (UAVs), some detrimental factors, like occlusion, significantly impact target detection performance. Active object detection (AOD) offers an effective way to address it, which usually uses deep… read more here.
Keywords: detection; active object; representation; state representation ... See more keywords
Active Object Detection Based on a Novel Deep Q-Learning Network and Long-Term Learning Strategy for the Service Robot
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Industrial Electronics"
DOI: 10.1109/tie.2021.3090707
Abstract: This article focuses on active object detection (AOD), one of the greatest challenges in the robotics field. A novel deep-Q-learning-network-based approach is proposed to utilize more useful status information for enhancing the training efficiency and… read more here.
Keywords: active object; deep learning; strategy; novel deep ... See more keywords
Long-Term Active Object Detection for Service Robots: Using Generative Adversarial Imitation Learning With Contextualized Memory Graph
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DOI: 10.1109/tie.2024.3468636
Abstract: Active object detection (AOD) is a crucial task in embodied artificial intelligence within robotics. Previous works mainly address this challenge through deep reinforcement learning (DRL), characterized by prolonged training cycles and model convergence difficulties. Moreover,… read more here.
Keywords: active object; adversarial imitation; memory; object detection ... See more keywords
Active Object Discovery and Localization Using Sound-Induced Attention
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DOI: 10.1109/tii.2020.3000240
Abstract: Industrial intelligent devices are usually equipped with both microphones and cameras to perceive and understand the physical world. Though visual object detection technology has achieved a great success, its combination with other sensing modalities remains… read more here.
Keywords: object discovery; sound induced; active object; induced attention ... See more keywords