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检索条件"主题词=Deep Learning for Visual Perception"
437 条 记 录,以下是71-80 订阅
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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
来源: 评论
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
来源: 评论
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
来源: 评论
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
来源: 评论
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
来源: 评论
Event-Driven Force Measurement of a Variable-Stiffness Robotic Finger Using Masked Autoencoder Pre-Training
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IEEE ROBOTICS AND AUTOMATION LETTERS 2025年 第6期10卷 5831-5838页
作者: Guo, Qianyu Lu, Yawen Fu, Jiaming Gan, Dongming Purdue Univ Sch Engn Technol W Lafayette IN 47906 USA Purdue Univ Comp Graph Technol Dept W Lafayette IN 47906 USA Univ West Florida Mech Engn Dept Pensacola FL 32514 USA
Force feedback in compliant robotic grippers is essential for precise manipulation tasks but remains challenging because irregular deformation of soft materials renders traditional sensor integration impractical. Even... 详细信息
来源: 评论
LatentBKI: Open-Dictionary Continuous Mapping in visual-Language Latent Spaces With Quantifiable Uncertainty
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IEEE ROBOTICS AND AUTOMATION LETTERS 2025年 第4期10卷 3102-3109页
作者: Wilson, Joey Xu, Ruihan Sun, Yile Ewen, Parker Zhu, Minghan Barton, Kira Ghaffari, Maani Univ Michigan Ann Arbor MI 48109 USA
This letter introduces a novel probabilistic mapping algorithm, LatentBKI, which enables open-vocabulary mapping with quantifiable uncertainty. Traditionally, semantic mapping algorithms focus on a fixed set of semant... 详细信息
来源: 评论
ConditionNET: learning Preconditions and Effects for Execution Monitoring
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IEEE ROBOTICS AND AUTOMATION LETTERS 2025年 第2期10卷 1337-1344页
作者: Sliwowski, Daniel Lee, Dongheui Tech Univ Wien TU Wien Autonomous Syst Lab A-1040 Vienna Austria Inst Robot & Mechatron DLR German Aerosp Ctr D-82234 Wessling Germany
The introduction of robots into everyday scenarios necessitates algorithms capable of monitoring the execution of tasks. In this letter, we propose ConditionNET, an approach for learning the preconditions and effects ... 详细信息
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