检索结果-内蒙古大学图书馆

2023 IEEE/CVF Conference on computer vision and pattern recognition Workshops, CVPRW 2023

作者： Phutke, Shruti S. Kulkarni, Ashutosh Vipparthi, Santosh Kumar Murala, Subrahmanyam Indian Institute of Technology Ropar Computer Vision and Pattern Recognition Lab Punjab Rupnagar India

ISBN: (纸本)9798350302493

Blind image inpainting is a crucial restoration task that does not demand additional mask information to restore the corrupted regions. Yet, it is a very less explored research area due to the difficulty in discriminating between corrupted and valid regions. There exist very few approaches for blind image inpainting which sometimes fail at producing plausible inpainted images. Since they follow a common practice of predicting the corrupted regions and then inpaint them. To skip the corrupted region prediction step and obtain better results, in this work, we propose a novel end-to-end architecture for blind image inpainting consisting of wavelet query multi-head attention transformer block and the omni-dimensional gated attention. The proposed wavelet query multi-head attention in the transformer block provides encoder features via processed wavelet coefficients as query to the multi-head attention. Further, the proposed omni-dimensional gated attention effectively provides all dimensional attentive features from the encoder to the respective decoder. Our proposed approach is compared numerically and visually with existing state-of-the-art methods for blind image inpainting on different standard datasets. The comparative and ablation studies prove the effectiveness of the proposed approach for blind image inpainting. The testing code is available at : https://***/shrutiphutke/Blind-Omni-Wav-Net © 2023 IEEE.

关键词： Restoration

来源：评论

学校读者我要写书评

暂无评论

Revisiting the Generalization Problem of Low-level vision Models Through the Lens of Image Deraining

arXiv

引用

arXiv 2025年

作者： Hu, Jinfan You, Zhiyuan Gu, Jinjin Zhu, Kaiwen Xue, Tianfan Dong, Chao Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China University of Chinese Academy of Sciences Beijing100049 China The Chinese University of Hong Kong 999077 Hong Kong The University of Sydney NSW2006 Australia Shanghai Jiao Tong University Shanghai200240 China Shanghai Artificial Intelligence Laboratory Shanghai200232 China Shenzhen Key Lab of Computer Vision and Pattern Recognition Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China Shenzhen University of Advanced Technology Shenzhen518055 China

Generalization remains a significant challenge for low-level vision models, which often struggle with unseen degradations in real-world scenarios despite their success in controlled benchmarks. In this paper, we revisit the generalization problem in low-level vision models. Image deraining is selected as a case study due to its well-defined and easily decoupled structure, allowing for more effective observation and analysis. Through comprehensive experiments, we reveal that the generalization issue is not primarily due to limited network capacity but rather the failure of existing training strategies, which lead networks to overfit specific degradation patterns. Our findings show that guiding networks to focus on learning the underlying image content, rather than the degradation patterns, is key to improving generalization. We demonstrate that balancing the complexity of background images and degradations in the training data helps networks better fit the image distribution. Furthermore, incorporating content priors from pre-trained generative models significantly enhances generalization. Experiments on both image deraining and image denoising validate the proposed strategies. We believe the insights and solutions will inspire further research and improve the generalization of low-level vision models. Copyright © 2025, The Authors. All rights reserved.

关键词： Image denoising

来源：评论

学校读者我要写书评

暂无评论

Convex relaxations for binary image partitioning and perceptual grouping 23rd

引用

23rd German Association for pattern recognition Symposium, DAGM 2001

作者： Keuchel, Jens Schellewald, Christian Cremers, Daniel Schnörr, Christoph Computer Vision Graphics and Pattern Recognition Group Department of Mathematics and Computer Science University of Mannheim MannheimD-68131 Germany

ISBN: (纸本)3540425969

We consider approaches to computer vision problems which require the minimization of a global energy functional over binary variables and take into account both local similarity and spatial context. The combinatorial nature of such problems has lead to the design of various approximation algorithms in the past which often involve tuning parameters and tend to get trapped in local minima. In this context, we present a novel approach to the field of computer vision that amounts to solving a convex relaxation of the original problem without introducing any additional parameters. Numerical ground truth experiments reveal a relative error of the convex minimizer with respect to the global optimum of below 2% on the average. We apply our approach by discussing two specific problem instances related to image partitioning and perceptual grouping. Numerical experiments illustrate the quality of the approach which, in the partitioning case, compares favorably with established approaches like the ICM-algorithm. © Springer-Verlag Berlin Heidelberg 2001.

关键词： Approximation algorithms

来源：评论

学校读者我要写书评

暂无评论

Motion competition: Variational integration of motion segmentation and shape regularization

Motion competition: Variational integration of motion segmen...

引用

24th German Association for pattern recognition Symposium, DAGM 2002

作者： Cremers, Daniel Schnörr, Christoph Computer Vision Graphics and Pattern Recognition Group Department of Mathematics and Computer Science University of Mannheim MannheimD–68131 Germany

ISBN: (纸本)354044209X

We present a variational method for the segmentation of piecewise affine flow fields. Compared to other approaches to motion segmentation, we minimize a single energy functional both with respect to the affine motion models in the separate regions and with respect to the shape of the separating contour. In the manner of region competition, the evolution of the segmenting contour is driven by a force which aims at maximizing a homogeneity measure with respect to the estimated motion in the adjoining regions. We compare segmentations obtained for the models of piecewise affine motion, piecewise constant motion, and piecewise constant intensity. For objects which cannot be discriminated from the background by their appearance, the desired motion segmentation is obtained, although the corresponding segmentation based on image intensities fails. The region– based formulation facilitates convergence of the contour from its initialization over fairly large distances, and the estimated discontinuous flow field is progressively improved during the gradient descent minimization. By including in the variational method a statistical shape prior, the contour evolution is restricted to a subspace of familiar shapes, such that a robust estimation of irregularly moving shapes becomes feasible. © Springer-Verlag Berlin Heidelberg 2002.

关键词： Flow fields

来源：评论

学校读者我要写书评

暂无评论

On-ine variational estimation of dynamical fluid flows with physics-based spatio-temporal regularization

引用

28th Symposium of the German Association for pattern recognition, DAGM 2006

作者： Ruhnau, Paul Stahl, Annette Schnörr, Christoph Computer Vision Graphics and Pattern Recognition Group Department of Mathematics and Computer Science University of Mannheim D-68131 Mannheim Germany

ISBN: (纸本)3540444122

We present a variational approach to motion estimation of instationary fluid flows. Our approach extends prior work along two directions;(i) The full incompressible Navier-Stokes equation is employed in order to obtain a physically consistent regularization which does not suppress turbulent flow variations, (ii) Regularization along the time-axis is employed as well, but formulated in a receding horizon manner contrary to previous approaches to spatio-temporal regularization. This allows for a recursive on-line (non-batch) implementation of our estimation framework. Ground-truth evaluations for simulated turbulent flows demonstrate that due to imposing both physical consistency and temporal coherency, the accuracy of flow estimation compares favourably even with optical flow approaches based on higher-order div-curl regularization. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Flow of fluids

来源：评论

学校读者我要写书评

暂无评论

TSNet: Deep Network for Human Action recognition in Hazy Videos

TSNet: Deep Network for Human Action Recognition in Hazy Vid...

引用

2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018

作者： Chaudhary, Sachin Murala, Subrahmanyam Computer Vision and Pattern Recognition Lab Depatment of Electrical Engineering Indian Institute of Technology Ropar India

ISBN: (纸本)9781538666500

The all-weather intelligent surveillance system is the prime challenge for computer vision researchers. The surveillance is mostly done to analyze the human activity in a particular region. Several extreme weather conditions like rain, snow, haze, fog etc. halts the surveillance process and thus decreases the reliability of the surveillance system. Here, an attempt is made to tackle one of these weather situation i.e. haze in case of surveillance. Haze distorts the quality of images and videos captured by camera. Due to poor quality, it is difficult to analyze the haze degraded video for the human activities using the existing state-of-the-art methods for human action recognition (HAR). Therefore, in this paper, a new two level saliency based end-to-end network (TSNet) for HAR in hazy videos is proposed. De-hazing approaches given in [1]-[9] have certain limitations and therefore we fine-tuned the de-hazing network given in [10] for HAR. The concept of rank pooling given in [11] is further utilized to efficiently represent the temporal saliency of the video. The transmission map information is utilized here to fix the spatial saliency in each frame. As currently, there is no dataset available for HAR in hazy video, here a new dataset of hazy video is generated from two benchmark datasets namely HMDB51 [12] and UCF101 [13] by adding synthetic haze. The existing methods for HAR proposed in [11], [14], [15] are applied and compared with the proposed method on proposed hazy-HMDB51 and hazy-UCF101. The proposed method clearly outperforms the above mentioned methods in terms of average recognition rate (ARR). © 2018 IEEE.

关键词： Monitoring

来源：评论

学校读者我要写书评

暂无评论

Novel human computer interaction principles for cardiac feedback using google glass and Android wear 12

Novel human computer interaction principles for cardiac feed...

引用

12th IEEE International Conference on Wearable and Implantable Body Sensor Networks, BSN 2015

作者： Richer, Robert Maiwald, Tim Pasluosta, Cristian Hensel, Bernhard Eskofier, Bjoern M. Digital Sports Group Pattern Recognition Lab Department of Computer Science Germany Erlangen Germany

ISBN: (纸本)9781467372015

This work presents a system for unobtrusive cardiac feedback in daily life. It addresses the whole pipeline from data acquisition over data processing to data visualization including wearable integration. ECG signals are recorded with a novel ECG sensor supporting Bluetooth Low Energy, which is able to transmit raw ECG data as well as estimated heart rate. ECG signals are processed in real-time on a mobile device to automatically classify the user;s heart beats. A novel application for Android-based mobile devices was developed for data visualization. It offers several modes for cardiac feedback, from measuring the current heart rate to continuously monitoring the user;s heart status. It also allows to store acquired data in an internal database as well as in the Google Fit platform. Further, the application provides extensions for wearables like Google Glass and smartwatches running on Android Wear. Hardware performance evaluation was performed by comparing the course of heart rate between the novel ECG sensor and a commercial ECG sensor. The mean absolute error between the two sensors was 4.83 bpm with a standard deviation of 4.46 bpm, and a Pearson correlation of 0.922. A qualitative evaluation was performed for the Android application with special emphasis on the daily usability and the wearable integration. When the Google Glass was integrated, the subjects rated the application as 2.8/5 (0 = Bad, 5 = Excellent), whereas when the application was integrated with a smartwatch the rating increased to 4.2/5. © 2015 IEEE.

关键词： Feedback

来源：评论

学校读者我要写书评

暂无评论

Evaluation of convex optimization techniques for the weighted graph-matching problem in computer vision

引用

23rd German Association for pattern recognition Symposium, DAGM 2001

作者： Schellewald, Christian Roth, Stefan Schnörr, Christoph Computer Vision Graphics and Pattern Recognition Group Dept Mathematics and Computer Science University of Mannheim MannheimD-68131 Germany

ISBN: (纸本)3540425969

We present a novel approach to the weighted graph-matching problem in computer vision, based on a convex relaxation of the underlying combinatorial optimization problem. The approach always computes a lower bound of the objective function, which is a favorable property in the context of exact search algorithms. Furthermore, no tuning parameters have to be selected by the user, due to the convexity of the relaxed problem formulation. For comparison, we implemented a recently published deterministic annealing approach and conducted numerous experiments for both established benchmark experiments from combinatorial mathematics, and for random ground-truth experiments using computer-generated graphs. Our results show similar performance for both approaches. In contrast to the convex approach, however, four parameters have to be determined by hand for the annealing algorithm to become competitive. © Springer-Verlag Berlin Heidelberg 2001.

关键词： computer vision

来源：评论

学校读者我要写书评

暂无评论

Classification of daily life activities by decision level fusion of inertial sensor data 13

Classification of daily life activities by decision level fu...

引用

8th International Conference on Body Area Networks, BODYNETS 2013

作者： Schuldhaus, Dominik Leutheuser, Heike Eskofier, Bjoern M. Department of Computer Science Pattern Recognition Lab Digital Sports Group University Erlangen-Nuremberg Germany

ISBN: (纸本)9781936968893

The fusion of inertial sensor data is heavily used for the classification of daily life activities. The knowledge about the performed daily life activities is mandatory to give physically inactive people feedback about their individual quality of life. In this paper, four inertial sensors were placed on wrist, chest, hip and ankle of 19 subjects, which had to perform seven daily life activities. Each sensor node separately performed preprocessing, feature extraction and classification. In the final step, the classifier decisions of the sensor nodes were fused and a single activity was predicted by majority voting. The proposed classification system obtained an overall mean classification rate of 93.9 % and was robust against defect sensors. The system allows an easy integration of new sensors without retraining of the complete system, which is an advantage over commonly used feature level fusion approaches. © 2013 ICST 978-1-936968-89-3.

关键词： Sensor nodes

来源：评论

学校读者我要写书评

暂无评论

Human-focused computer vision applications

Human-focused computer vision applications

引用

International Conference on computer Graphics, Imaging and Visualisation, CGIV'06

作者： Piccardi, Massimo Department of Computer Systems Faculty of IT University of Technology Sydney Australia UTS Computer Vision Research Group IEEE IEEE Computer Society International Association for Pattern Recognition

ISBN: (纸本)0769526063

Recent years have seen an increasing number of computer vision applications focusing on humans as their objects of interest. Such applications include video surveillance, domotics, multimedia semantic annotation and indexing, human-computer interfaces, affective computing, just to cite a few. What exactly are their "objects of interest"? A broad range of human-related features: motion, gestures, actions, interactions, activities, attitudes, behaviours, identity. This keynote will offer a survey of this field and present some current work from the speaker and his collaborators in the areas of emotion recognition and people tracking within camera networks. © 2006 IEEE.

关键词： computer vision

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：