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检索条件"主题词=Deep Learning for Visual Perception"
437 条 记 录,以下是31-40 订阅
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Mobile Manipulation Instruction Generation From Multiple Images With Automatic Metric Enhancement
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IEEE ROBOTICS AND AUTOMATION LETTERS 2025年 第3期10卷 3022-3029页
作者: Katsumata, Kei Kambara, Motonari Yashima, Daichi Korekata, Ryosuke Sugiura, Komei Keio Univ Yokohama Kanagawa 2238522 Japan
We consider the problem of generating free-form mobile manipulation instructions based on a target object image and receptacle image. Conventional image captioning models are not able to generate appropriate instructi... 详细信息
来源: 评论
BiCo-Fusion: Bidirectional Complementary LiDAR-Camera Fusion for Semantic- and Spatial-Aware 3D Object Detection
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IEEE ROBOTICS AND AUTOMATION LETTERS 2025年 第2期10卷 1457-1464页
作者: Song, Yang Wang, Lin Hong Kong Univ Sci & Technol Guangzhou AI Thrust Guangzhou 511458 Guangdong Peoples R China Nanyang Technol Univ NTU Sch Elect & Elect Engn EEE Singapore 639798 Singapore
3D object detection is an important task that has been widely applied in autonomous driving. To perform this task, a new trend is to fuse multi-modal inputs, i.e., LiDAR and camera. Under such a trend, recent methods ... 详细信息
来源: 评论
OMEGA: Efficient Occlusion-Aware Navigation for Air-Ground Robots in Dynamic Environments via State Space Model
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IEEE ROBOTICS AND AUTOMATION LETTERS 2025年 第2期10卷 1066-1073页
作者: Wang, Junming Guan, Xiuxian Sun, Zekai Shen, Tianxiang Huang, Dong Liu, Fangming Cui, Heming Univ Hong Kong Hong Kong Peoples R China Huazhong Univ Sci & Technol Peng Cheng Lab Wuhan 430074 Peoples R China Shanghai AI Labolatory Shanghai 200232 Peoples R China
Air-ground robots (AGRs) are widely used in surveillance and disaster response due to their exceptional mobility and versatility (i.e., flying and driving). Current AGR navigation systems perform well in static occlus... 详细信息
来源: 评论
DreamUp3D: Object-Centric Generative Models for Single-View 3D Scene Understanding and Real-to-Sim Transfer
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IEEE ROBOTICS AND AUTOMATION LETTERS 2024年 第4期9卷 3291-3298页
作者: Wu, Yizhe Borde, Haitz Saez de Ocariz Collins, Jack Jones, Oiwi Parker Posner, Ingmar Oxford Robot Inst Appl AI Lab Oxford OX1 2JH England
3D scene understanding for robotic applications exhibits a unique set of requirements including real-time inference, object-centric latent representation learning, accurate 6D pose estimation and 3D reconstruction of ... 详细信息
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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
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Towards Better Data Exploitation in Self-Supervised Monocular Depth Estimation
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IEEE ROBOTICS AND AUTOMATION LETTERS 2024年 第1期9卷 763-770页
作者: Liu, Jinfeng Kong, Lingtong Yang, Jie Liu, Wei Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China
Depth estimation plays an important role in robotic perception systems. The self-supervised monocular paradigm has gained significant attention since it can free training from the reliance on depth annotations. Despit... 详细信息
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Co-Occ: Coupling Explicit Feature Fusion With Volume Rendering Regularization for Multi-Modal 3D Semantic Occupancy Prediction
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IEEE ROBOTICS AND AUTOMATION LETTERS 2024年 第6期9卷 5687-5694页
作者: Pan, Jingyi Wang, Zipeng Wang, Lin Hong Kong Univ Sci & Technol AI Thrust Guangzhou 511458 Guangdong Peoples R China Hong Kong Univ Sci & Technol AI CMA Thrust Guangzhou 511458 Guangdong Peoples R China Hong Kong Univ Sci & Technol Dept CSE Hong Kong Peoples R China
3D semantic occupancy prediction is a pivotal task in the field of autonomous driving. Recent approaches have made great advances in 3D semantic occupancy predictions on a single modality. However, multi-modal semanti... 详细信息
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Collaborative Multi-Object Tracking With Conformal Uncertainty Propagation
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IEEE ROBOTICS AND AUTOMATION LETTERS 2024年 第4期9卷 3323-3330页
作者: Su, Sanbao Han, Songyang Li, Yiming Zhang, Zhili Feng, Chen Ding, Caiwen Miao, Fei Univ Connecticut Dept Comp Sci & Engn Storrs CT 06268 USA Univ Connecticut Storrs CT 06268 USA NYU Tandon Sch Engn Brooklyn NY 11201 USA
Object detection and multiple object tracking (MOT) are essential components of self-driving systems. Accurate detection and uncertainty quantification are both critical for onboard modules, such as perception, predic... 详细信息
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learning Rearrangement Manipulation via Scene Prediction in Point Cloud
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IEEE ROBOTICS AND AUTOMATION LETTERS 2024年 第12期9卷 11090-11097页
作者: Ma, Anji Duan, Xingguang Beijing Inst Technol Sch Mechatron Engn Beijing 100081 Peoples R China
Predicting scene evolution conditioned on robotic actions is a vital technique in modeling robot manipulations. Previous studies have primarily focused on learning spatiotemporally continuous actions like Cartesian di... 详细信息
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learning-To-Rank Approach for Identifying Everyday Objects Using a Physical-World Search Engine
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IEEE ROBOTICS AND AUTOMATION LETTERS 2024年 第3期9卷 2088-2095页
作者: Kaneda, Kanta Nagashima, Shunya Korekata, Ryosuke Kambara, Motonari Sugiura, Komei Keio Univ Yokohama 2238522 Japan
Domestic service robots offer a solution to the increasing demand for daily care and support. A human-in-the-loop approach that combines automation and operator intervention is considered to be a realistic approach to... 详细信息
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