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检索条件"主题词=Deep Learning for Visual Perception"
436 条 记 录,以下是31-40 订阅
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Semi-supervised generative adversarial network to estimate the depth map of underwater targets in acoustic images for 3D reconstruction
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MEASUREMENT SCIENCE AND TECHNOLOGY 2025年 第3期36卷 035403-035403页
作者: Bai, Boming Yan, Weisheng Cui, Rongxin Northwestern Polytech Univ Sch Marine Sci & Technol Xian 710072 Peoples R China
Owing to the unique imaging formulation principle of acoustic cameras, certain dimensions of the target may be lost in acoustic images. Some studies have been conducted to retrieve these missing details from a single ... 详细信息
来源: 评论
See-Touch-Predict: Active Exploration and Online perception of Terrain Physics With Legged Robots
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IEEE ROBOTICS AND AUTOMATION LETTERS 2025年 第4期10卷 3470-3477页
作者: Lin, Huangxuan Li, Haoyang Gao, Yue Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ MoE Key Lab Artificial Intelligence Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ AI Inst Shanghai 200240 Peoples R China
Assessing physical properties of the environment with vision helps humans to respond appropriately before entering risky areas. However, equipping robots with such perceptual ability is challenging due to the lack of ... 详细信息
来源: 评论
EdgeFlowNet: 100FPS@1W Dense Optical Flow for Tiny Mobile Robots
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IEEE ROBOTICS AND AUTOMATION LETTERS 2025年 第1期10卷 128-135页
作者: Pinnama Raju, Sai Ramana Kiran Singh, Rishabh Velmurugan, Manoj Jagannatha Sanket, Nitin Worcester Polytech Inst Percept & Autonomous Robot PeAR Grp Robot Engn Worcester MA 01609 USA
Optical flow estimation is a critical task for tiny mobile robotics to enable safe and accurate navigation, obstacle avoidance, and other functionalities. However, optical flow estimation on tiny robots is challenging... 详细信息
来源: 评论
Stereo-Based 3D Human Pose Estimation for Underwater Robots Without 3D Supervision
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IEEE ROBOTICS AND AUTOMATION LETTERS 2025年 第5期10卷 5002-5009页
作者: Wu, Ying-Kun Sattar, Junaed Univ Minnesota Twin Cities Dept Comp Sci & Engn Minneapolis MN 55455 USA Univ Minnesota Twin Cities Minnesota Robot Inst MnRI Minneapolis MN 55455 USA
In this paper, we propose a novel deep learning-based 3D underwater human pose estimator capable of providing metric 3D poses of scuba divers from stereo image pairs. While existing research has made significant advan... 详细信息
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InstantPose: Zero-Shot Instance-Level 6D Pose Estimation From a Single View
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IEEE ROBOTICS AND AUTOMATION LETTERS 2025年 第6期10卷 6023-6030页
作者: Di Felice, Francesco Remus, Alberto Gasperini, Stefano Busam, Benjamin Ott, Lionel Thalhammer, Stefan Tombari, Federico Avizzano, Carlo Alberto Scuola Super Sant Anna Mech Intelligence Inst Dept Excellence Robot & AI I-56124 Pisa Italy Leonardo SpA Robot Lab Innovat Hub &I ntellectual Property I-16149 Genoa Italy Tech Univ Munich TUM Sch Computat Informat & Technol D-80809 Munich Germany Swiss Fed Inst Technol Dept Mech & Proc Engn Autonomous Syst Lab CH-8092 Zurich Switzerland UAS Tech Vienna Ind Engn Dept A-1040 Vienna Austria Google Zurich CH-8092 Zurich Switzerland
Object pose estimation using visual data is crucial for robotic interaction with the environment. Many existing instance-level methods are restricted by their requirements for 3D CAD models or multiple object views, w... 详细信息
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MonoTher-Depth: Enhancing Thermal Depth Estimation via Confidence-Aware Distillation
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IEEE ROBOTICS AND AUTOMATION LETTERS 2025年 第3期10卷 2830-2837页
作者: Zuo, Xingxing Ranganathan, Nikhil Lee, Connor Gkioxari, Georgia Chung, Soon-Jo CALTECH Pasadena CA 91125 USA
Monocular depth estimation (MDE) from thermal images is a crucial technology for robotic systems operating in challenging conditions such as fog, smoke, and low light. The limited availability of labeled thermal data ... 详细信息
来源: 评论
Exploiting Motion Prior for Accurate Pose Estimation of Dashboard Cameras
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IEEE ROBOTICS AND AUTOMATION LETTERS 2025年 第1期10卷 764-771页
作者: Lu, Yipeng Zhao, Yifan Wang, Haiping Ruan, Zhiwei Liu, Yuan Dong, Zhen Yang, Bisheng Wuhan Univ State Key Lab Informat Engn Surveying Mapping & Re Wuhan 430072 Peoples R China China Univ Geosci Wuhan 430079 Peoples R China Didi Chuxing Technol Co Beijing 100193 Peoples R China Hong Kong Univ Sci & Technol Hong Kong Peoples R China Nanyang Technol Univ Singapore 639798 Singapore
Dashboard cameras (dashcams) record millions of driving videos daily, offering a valuable potential data source for various applications, including driving map production and updates. A necessary step for utilizing th... 详细信息
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Bayesian NeRF: Quantifying Uncertainty With Volume Density for Neural Implicit Fields
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IEEE ROBOTICS AND AUTOMATION LETTERS 2025年 第3期10卷 2144-2151页
作者: Lee, Sibaek Kang, Kyeongsu Ha, Seongbo Yu, Hyeonwoo Sungkyunkwan Univ Dept Intelligent Robot Suwon 12345 South Korea
We present a Bayesian Neural Radiance Field (NeRF), which explicitly quantifies uncertainty in the volume density by modeling uncertainty in the occupancy, without the need for additional networks, making it particula... 详细信息
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Pair-VPR: Place-Aware Pre-Training and Contrastive Pair Classification for visual Place Recognition With Vision Transformers
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IEEE ROBOTICS AND AUTOMATION LETTERS 2025年 第4期10卷 4013-4020页
作者: Hausler, Stephen Moghadam, Peyman CSIRO CSIRO Robot Data61 Brisbane Qld 4069 Australia Queensland Univ Technol QUT Sch Elect Engn & Robot Brisbane 4069 Australia
In this work we propose a novel joint training method for visual Place Recognition (VPR), which simultaneously learns a global descriptor and a pair classifier for re-ranking. The pair classifier can predict whether a... 详细信息
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Taxonomy-Aware Continual Semantic Segmentation in Hyperbolic Spaces for Open-World perception
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IEEE ROBOTICS AND AUTOMATION LETTERS 2025年 第2期10卷 1904-1911页
作者: Hindel, Julia Cattaneo, Daniele Valada, Abhinav Univ Freiburg Dept Comp Sci D-79110 Freiburg Germany
Semantic segmentation models are typically trained on a fixed set of classes, limiting their applicability in open-world scenarios. Class-incremental semantic segmentation aims to update models with emerging new class... 详细信息
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