作者: 拒絕 時(shí)間: 2025-3-21 20:32
TBPos: Dataset for?Large-Scale Precision Visual Localizationnd truth poses: both the database images and the query images have been derived from the same laser scanner data. In the experimental part of the paper, the proposed dataset is evaluated by means of an image-based localization pipeline.作者: 錯(cuò)事 時(shí)間: 2025-3-22 00:58 作者: alcohol-abuse 時(shí)間: 2025-3-22 05:41 作者: opportune 時(shí)間: 2025-3-22 11:55
BrackishMOT: The Brackish Multi-Object Tracking Datasetmework for creating synthetic sequences in order to expand the dataset. The framework consists of animated fish models and realistic underwater environments. We analyse the effects of including synthetic data during training and show that a combination of real and synthetic underwater training data can enhance tracking performance. . ..作者: cipher 時(shí)間: 2025-3-22 15:22
Improved Sensitivity of No-Reference Image Visual Quality Metrics to the Presence of Noiseproposed by combining this metric with a noise level estimator. The proposed method allows to significantly decrease a probability of wrong quality predictions for noisy images. Efficiency of usage of different noise level estimators in the proposed combined metrics is analyzed.作者: 不真 時(shí)間: 2025-3-22 19:32
Conference proceedings 2023ction, recognition, classification, and localization in 2D and/or 3D; machine learning and deep learning; segmentation, grouping, and shape; vision for robotics and autonomous vehicles; biometrics, faces, body gestures and pose; 3D vision from multiview and other sensors; vision applications and systems..作者: Analogy 時(shí)間: 2025-3-22 23:48 作者: FRONT 時(shí)間: 2025-3-23 03:15
Conference proceedings 2023Lapland, Finland, in April 2023..The 67 revised papers presented were carefully reviewed and selected from 108 submissions. The contributions are structured in topical sections on datasets and evaluation; action and behaviour recognition; image and video processing, analysis, and understanding; dete作者: 衰老 時(shí)間: 2025-3-23 06:45
chemical signals in their environments, or chemotaxis, can be clearly seen as a major force in cell biology. In .Chemotaxis: Methods and Protocols., expert researchers in the field provide state-of-the-art methods for investigating cell migration behaviors, studying molecular components involved in 作者: aerobic 時(shí)間: 2025-3-23 10:28
fish, neurons, and immune and tumor cells.Examines phenomena.Fundamental to the development and vital functions of organisms, the migration of motile cells due to the detection of shallow gradients of specific chemical signals in their environments, or chemotaxis, can be clearly seen as a major forc作者: LAP 時(shí)間: 2025-3-23 15:54
Jukka Peltom?ki,Farid Alijani,Jussi Puura,Heikki Huttunen,Esa Rahtu,Joni-Kristian K?m?r?inenchemical signals in their environments, or chemotaxis, can be clearly seen as a major force in cell biology. In .Chemotaxis: Methods and Protocols., expert researchers in the field provide state-of-the-art methods for investigating cell migration behaviors, studying molecular components involved in 作者: 整潔 時(shí)間: 2025-3-23 18:43 作者: Capitulate 時(shí)間: 2025-3-24 00:26 作者: 擺動(dòng) 時(shí)間: 2025-3-24 02:55
Armin Danesh Pazho,Ghazal Alinezhad Noghre,Babak Rahimi Ardabili,Christopher Neff,Hamed Tabkhichemical signals in their environments, or chemotaxis, can be clearly seen as a major force in cell biology. In .Chemotaxis: Methods and Protocols., expert researchers in the field provide state-of-the-art methods for investigating cell migration behaviors, studying molecular components involved in 作者: dapper 時(shí)間: 2025-3-24 06:50
Saqib Nazir,Zhouyan Qiu,Daniela Coltuc,Joaquín Martínez-Sánchez,Pedro Ariaschemical signals in their environments, or chemotaxis, can be clearly seen as a major force in cell biology. In .Chemotaxis: Methods and Protocols., expert researchers in the field provide state-of-the-art methods for investigating cell migration behaviors, studying molecular components involved in 作者: REIGN 時(shí)間: 2025-3-24 13:14 作者: Modify 時(shí)間: 2025-3-24 17:36 作者: 事與愿違 時(shí)間: 2025-3-24 20:32
Ekaterina Nepovinnykh,Antti Vilkman,Tuomas Eerola,Heikki K?lvi?inenchemical signals in their environments, or chemotaxis, can be clearly seen as a major force in cell biology. In .Chemotaxis: Methods and Protocols., expert researchers in the field provide state-of-the-art methods for investigating cell migration behaviors, studying molecular components involved in 作者: anaerobic 時(shí)間: 2025-3-25 01:43 作者: osteopath 時(shí)間: 2025-3-25 05:12 作者: REP 時(shí)間: 2025-3-25 08:19
Cuong Le,Xin Liufish, neurons, and immune and tumor cells.Examines phenomena.Fundamental to the development and vital functions of organisms, the migration of motile cells due to the detection of shallow gradients of specific chemical signals in their environments, or chemotaxis, can be clearly seen as a major forc作者: Genteel 時(shí)間: 2025-3-25 14:39 作者: Feigned 時(shí)間: 2025-3-25 17:55 作者: Obsequious 時(shí)間: 2025-3-25 22:38 作者: 主講人 時(shí)間: 2025-3-26 03:51
Subhashis Banerjee,Robin Strandchemical signals in their environments, or chemotaxis, can be clearly seen as a major force in cell biology. In .Chemotaxis: Methods and Protocols., expert researchers in the field provide state-of-the-art methods for investigating cell migration behaviors, studying molecular components involved in 作者: Coronary 時(shí)間: 2025-3-26 06:48 作者: 指派 時(shí)間: 2025-3-26 10:03
Juliette Bertrand,Yannis Kalantidis,Giorgos Toliaschemical signals in their environments, or chemotaxis, can be clearly seen as a major force in cell biology. In .Chemotaxis: Methods and Protocols., expert researchers in the field provide state-of-the-art methods for investigating cell migration behaviors, studying molecular components involved in 作者: indecipherable 時(shí)間: 2025-3-26 15:11
LiDAR Place Recognition Evaluation with?the?Oxford Radar RobotCar Dataset Revisedover the original Oxford RobotCar dataset since it has better LiDAR sensors and location ground truth is available for all sequences. However, it turns out that the Radar dataset has serious issues with its ground truth and therefore experimental findings with this dataset can be misleading. We demo作者: 不透明 時(shí)間: 2025-3-26 19:10
BrackishMOT: The Brackish Multi-Object Tracking Dataset the BrackishMOT dataset with focus on tracking schools of small fish, which is a notoriously difficult MOT task. BrackishMOT consists of 98 sequences captured in the wild. Alongside the novel dataset, we present baseline results by training a state-of-the-art tracker. Additionally, we propose a fra作者: 清澈 時(shí)間: 2025-3-26 23:47 作者: 鋼盔 時(shí)間: 2025-3-27 04:42
CHAD: Charlotte Anomaly Datasetrmine if specific frames of a video contain abnormal behaviors. However, video anomaly detection is particularly context-specific, and the availability of representative datasets heavily limits real-world accuracy. Additionally, the metrics currently reported by most state-of-the-art methods often d作者: BROOK 時(shí)間: 2025-3-27 07:04
iDFD: A Dataset Annotated for?Depth and?Defocusroposed to solve these two tasks separately, using Deep Learning (DL) powerful learning capability. However, when it comes to training the Deep Neural Networks (DNN) for image deblurring or Depth from Defocus (DFD), the mentioned methods are mostly based on synthetic training datasets because of the作者: 事物的方面 時(shí)間: 2025-3-27 13:02 作者: 閑蕩 時(shí)間: 2025-3-27 15:19 作者: drusen 時(shí)間: 2025-3-27 18:17 作者: BLAND 時(shí)間: 2025-3-28 00:11
Attention-guided Boundary Refinement on?Anchor-free Temporal Action Detectionndencies among features from different temporal locations. Additionally, based on the developed temporal attention unit, we propose an attention-guided boundary refinement module for revising action prediction results. Besides, we integrate the proposed module into a contemporary anchor-free detecto作者: 一美元 時(shí)間: 2025-3-28 03:52
Spatio-temporal Attention Graph Convolutions for?Skeleton-based Action Recognitionand the method has achieved excellent results recently. However, GCN-based techniques only focus on the spatial correlations between human joints and often overlook the temporal relationships. In an action sequence, the consecutive frames in a neighborhood contain similar poses and using only tempor作者: 廣口瓶 時(shí)間: 2025-3-28 07:07 作者: Directed 時(shí)間: 2025-3-28 11:59
To Quantify an?Image Relevance Relative to?a?Target 3D Objectd be both informative and offer a relevant view of the object, .a pose that presents the essential characteristic information about the 3D object. To estimate the quality of the view, we propose to rely on repeatable, second order features, extracted with a curvilinear saliency detector, in order to作者: 蛙鳴聲 時(shí)間: 2025-3-28 16:35 作者: 弄皺 時(shí)間: 2025-3-28 21:03 作者: 反省 時(shí)間: 2025-3-28 23:03
Rethinking Matching-Based Few-Shot Action Recognitioneither encodes such information in the representation itself and learns classifiers at test time, or obtains frame-level features and performs pairwise temporal matching. We first evaluate a number of matching-based approaches using features from spatio-temporal backbones, a comparison missing from 作者: 令人發(fā)膩 時(shí)間: 2025-3-29 06:29
Accuracy of?Parallel Distance Mapping Algorithms When Applied to?Sub-Pixel Precision Transformlculating the Euclidean Distance Transform on binary images, in order to achieve the highest accuracy as efficiently as possible. Less focus has been spent on perfecting algorithms calculating the Euclidean Distance Transform on non-binary images where a much higher degree of precision is made possi作者: ENNUI 時(shí)間: 2025-3-29 07:45 作者: DEFT 時(shí)間: 2025-3-29 14:53
978-3-031-31434-6The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl作者: Compatriot 時(shí)間: 2025-3-29 17:55
Image Analysis978-3-031-31435-3Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 時(shí)代 時(shí)間: 2025-3-29 21:44
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/i/image/461344.jpg作者: 陳腐的人 時(shí)間: 2025-3-30 03:47
step, readily reproducible laboratory protocols, and notes on troubleshooting and avoiding known pitfalls...Comprehensive and cutting-edge, .Chemotaxis: Methods and Protocols. serves scientists with practical guidance on the diverse methodologies that are currently propelling chemotaxis research for作者: 絕食 時(shí)間: 2025-3-30 06:25
Jukka Peltom?ki,Farid Alijani,Jussi Puura,Heikki Huttunen,Esa Rahtu,Joni-Kristian K?m?r?inenstep, readily reproducible laboratory protocols, and notes on troubleshooting and avoiding known pitfalls...Comprehensive and cutting-edge, .Chemotaxis: Methods and Protocols. serves scientists with practical guidance on the diverse methodologies that are currently propelling chemotaxis research for作者: Campaign 時(shí)間: 2025-3-30 10:09
Armin Danesh Pazho,Ghazal Alinezhad Noghre,Babak Rahimi Ardabili,Christopher Neff,Hamed Tabkhistep, readily reproducible laboratory protocols, and notes on troubleshooting and avoiding known pitfalls...Comprehensive and cutting-edge, .Chemotaxis: Methods and Protocols. serves scientists with practical guidance on the diverse methodologies that are currently propelling chemotaxis research for作者: FACET 時(shí)間: 2025-3-30 15:59 作者: 易改變 時(shí)間: 2025-3-30 19:06 作者: 萬(wàn)花筒 時(shí)間: 2025-3-30 22:15
step, readily reproducible laboratory protocols, and notes on troubleshooting and avoiding known pitfalls...Comprehensive and cutting-edge, .Chemotaxis: Methods and Protocols. serves scientists with practical guidance on the diverse methodologies that are currently propelling chemotaxis research for作者: Bereavement 時(shí)間: 2025-3-31 04:31 作者: Vsd168 時(shí)間: 2025-3-31 06:16 作者: 陶瓷 時(shí)間: 2025-3-31 09:11
Juliette Bertrand,Yannis Kalantidis,Giorgos Toliasstep, readily reproducible laboratory protocols, and notes on troubleshooting and avoiding known pitfalls...Comprehensive and cutting-edge, .Chemotaxis: Methods and Protocols. serves scientists with practical guidance on the diverse methodologies that are currently propelling chemotaxis research for作者: mydriatic 時(shí)間: 2025-3-31 13:54 作者: 擦試不掉 時(shí)間: 2025-3-31 18:39
Camera Calibration Without Camera Access - A Robust Validation Technique for?Extended PnP Methodsvalidation in experiments on synthetic data, simulating 2D detection and Lidar measurements. Additionally, we provide experiments using data from an actual scene and compare non-camera access and camera access calibrations. Last, we use our method to validate annotations in MegaDepth.作者: Dealing 時(shí)間: 2025-3-31 23:51
CHAD: Charlotte Anomaly Datasetch is useful for its lower computational demand in real-world settings. CHAD is also the first anomaly dataset to contain multiple views of the same scene. With four camera views and over 1.15 million frames, CHAD is the largest fully annotated anomaly detection dataset including person annotations,作者: Gratulate 時(shí)間: 2025-4-1 02:33 作者: HAUNT 時(shí)間: 2025-4-1 09:07 作者: Mercantile 時(shí)間: 2025-4-1 14:05 作者: 條約 時(shí)間: 2025-4-1 15:27
Spatio-temporal Attention Graph Convolutions for?Skeleton-based Action Recognition every time steps for skeleton-based action recognition. On two common datasets, the NTU-RGB+D60 and the NTU-RGB+D120, the proposed method achieved competitive classification results compared to state-of-the-art methods. The project’s GitHub page: ..
