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检索条件"任意字段=IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2015"

共 4931 条记录，以下是61-70 订阅

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Generation of Ground Truth for Object Detection While Playing an Online Game: Productive Gaming or Recreational Working?

Generation of Ground Truth for Object Detection While Playin...

引用

26th ieee conference on computer vision and pattern recognition (CVPR)

作者： Kavasidis, Isaak Spampinato, Concetto Giordano, Daniela Univ Catania Catania Italy

ISBN: (纸本)9780769549903

In this paper we present a flash game that aims at generating easily ground truth for testing object detection algorithms. Flash the Fish is an online game where the user is shown videos from underwater environments and has to take photos of fish by clicking on them. The initial ground truth is provided by object detection algorithms and, subsequent, cluster analysis and user evaluation techniques, allow for the generation of ground truth based on the weighted combination of these "photos". Evaluation of the platform and comparison of the obtained results against a hand drawn ground truth confirmed that reliable ground truth generation is not necessarily a cumbersome task both in terms of effort and time needed.

关键词： computer games object detection

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Bridging the Gap Between Automated and Human Facial Emotion Perception

Bridging the Gap Between Automated and Human Facial Emotion ...

引用

ieee/CVF conference on computer vision and pattern recognition (CVPR)

作者： Stratton, Derek Hand, Emily Univ Nevada Reno Reno NV 89557 USA

ISBN: (数字)9781665487399

ISBN: (纸本)9781665487399

Understanding the complex relationship between emotions and facial expressions is important for both psychologists and computer scientists. A large body of research in psychology investigates facial expressions, emotions, and how emotions are perceived from facial expressions. As computer scientists look to incorporate this research into automatic emotion perception systems, it is important to understand the nature and limitations of human emotion perception. These principles of emotion science affect the way datasets are created, methods are implemented, and results are interpreted in automated emotion perception. This paper aims to distill and align prior work in automated and human facial emotion perception to facilitate future discussions and research at the intersection of the two disciplines.

关键词： Emotion recognition computer vision Uncertainty conferences Sociology Psychology Natural language processing

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Importance is in your attention: agent importance prediction for autonomous driving

Importance is in your attention: agent importance prediction...

引用

ieee/CVF conference on computer vision and pattern recognition (CVPR)

作者： Hazard, Christopher Bhagat, Akshay Buddharaju, Balarama Raju Liu, Zhongtao Shao, Yunming Lu, Lu Omari, Sammy Cui, Henggang Motional Boston MA 02210 USA

ISBN: (数字)9781665487399

ISBN: (纸本)9781665487399

Trajectory prediction is an important task in autonomous driving. State-of-the-art trajectory prediction models often use attention mechanisms to model the interaction between agents. In this paper, we show that the attention information from such models can also be used to measure the importance of each agent with respect to the ego vehicle's future planned trajectory. Our experiment results on the nuPlans dataset show that our method can effectively find and rank surrounding agents by their impact on the ego's plan.

关键词： computer vision conferences Predictive models Trajectory pattern recognition Task analysis Autonomous vehicles

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Estimating (and fixing) the Effect of Face Obfuscation in Video recognition

Estimating (and <i>fixing</i>) the Effect of Face Obfuscatio...

引用

ieee/CVF conference on computer vision and pattern recognition (CVPR)

作者： Tomei, Matteo Baraldi, Lorenzo Bronzin, Simone Cucchiara, Rita Univ Modena & Reggio Emilia Modena Italy Metaliquid Srl Milan Italy

ISBN: (纸本)9781665448994

Recent research has shown that faces can be obfuscated in large-scale datasets with a minimal performance impact on image classification and downstream tasks like object recognition. In this paper, we investigate the role of face obfuscation in video classification datasets and quantify a more significant reduction in performance caused by face blurring. To reduce such performance effects, we propose a generalized distillation approach in which a privacy-preserving action recognition network is trained with privileged information given by face identities. We show, through experiments performed on Kinetics-400, that the proposed approach can fully close the performance gap caused by face anonymization.

关键词： Visualization computer vision Face recognition conferences Computational modeling Pipelines Object recognition

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3D Interaction environment for free view point TV and games using multiple tablet computers

3D Interaction environment for free view point TV and games ...

引用

26th ieee conference on computer vision and pattern recognition (CVPR)

作者： Dupre, Rob Acuna, Raul Herrera Argyriou, Vasileios Velastin, Sergio A.

ISBN: (纸本)9780769549903

The use of 3D technologies to represent elements and interact with them is an open and interesting research area. In this article we discuss a novel human computer interaction method that integrates mobile computing and 3D visualization techniques with applications on free viewpoint visualization and 3D rendering for interactive and realistic environments. Especially this approach is focused on augmented reality and home entertainment and it was developed and tested on mobiles and particularly on tablet computers. Finally, an evaluation mechanism on the accuracy of this interaction system is presented.

关键词： augmented reality human computer interaction interactive television mobile computing mobile television notebook computers

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Fine-grained Activity recognition in Baseball Videos 31

Fine-grained Activity Recognition in Baseball Videos

引用

ieee/CVF conference on computer vision and pattern recognition (CVPR)

作者： Piergiovanni, A. J. Ryoo, Michael S. Indiana Univ Dept Comp Sci Bloomington IN 47408 USA

ISBN: (数字)9781538661000

ISBN: (纸本)9781538661000

In this paper, we introduce a challenging new dataset, MLB-YouTube, designed for fine-grained activity detection. The dataset contains two settings: segmented video classification as well as activity detection in continuous videos. We experimentally compare various recognition approaches capturing temporal structure in activity videos, by classifying segmented videos and extending those approaches to continuous videos. We also compare models on the extremely difficult task of predicting pitch speed and pitch type from broadcast baseball videos. We find that learning temporal structure is valuable for fine-grained activity recognition.

关键词： Videos Activity recognition Sports Task analysis Cameras computer vision Games

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Automatic Signer Diarization - the Mover is the Signer Approach

Automatic Signer Diarization - the Mover is the Signer Appro...

引用

26th ieee conference on computer vision and pattern recognition (CVPR)

作者： Gebre, Binyam Gebrekidan Wittenburg, Peter Heskes, Tom Max Planck Inst Psycholinguist Nijmegen Netherlands Radboud Univ Nijmegen Nijmegen Netherlands

ISBN: (纸本)9780769549903

We present a vision-based method for signer diarization - the task of automatically determining "who signed when?" in a video. This task has similar motivations and applications as speaker diarization but has received little attention in the literature. In this paper, we motivate the problem and propose a method for solving it. The method is based on the hypothesis that signers make more movements than their interlocutors. Experiments on four videos (a total of 1.4 hours and each consisting of two signers) show the applicability of the method. The best diarization error rate (DER) obtained is 0.16.

关键词： computer vision gesture recognition image motion analysis object recognition video signal processing

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Tilted Cross-Entropy (TCE): Promoting Fairness in Semantic Segmentation

Tilted Cross-Entropy (TCE): Promoting Fairness in Semantic S...

引用

ieee/CVF conference on computer vision and pattern recognition (CVPR)

作者： Szabo, Attila Jamali-Rad, Hadi Mannava, Siva-Datta Shell Global Solut Int BV Amsterdam Netherlands Delft Univ Technol TU Delft Delft Netherlands

ISBN: (纸本)9781665448994

Traditional empirical risk minimization (ERM) for semantic segmentation can disproportionately advantage or disadvantage certain target classes in favor of an (unfair but) improved overall performance. Inspired by the recently introduced tilted ERM (TERM), we propose tilted cross-entropy (TCE) loss and adapt it to the semantic segmentation setting to minimize performance disparity among target classes and promote fairness. Through quantitative and qualitative performance analyses, we demonstrate that the proposed Stochastic TCE for semantic segmentation can offer improved overall fairness by efficiently minimizing the performance disparity among the target classes of Cityscapes.

关键词： computer vision conferences Semantics Performance analysis pattern recognition Risk management

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SCVRL: Shuffled Contrastive Video Representation Learning

SCVRL: Shuffled Contrastive Video Representation Learning

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ieee/CVF conference on computer vision and pattern recognition (CVPR)

作者： Dorkenwald, Michael Xiao, Fanyi Brattoli, Biagio Tighe, Joseph Modolo, Davide Heidelberg Univ Heidelberg Germany AWS AI Labs Palo Alto CA USA AWS Palo Alto CA USA

ISBN: (数字)9781665487399

ISBN: (纸本)9781665487399

We propose SCVRL, a novel contrastive-based framework for self-supervised learning for videos. Differently from previous contrast learning based methods that mostly focus on learning visual semantics (e.g., CVRL), SCVRL is capable of learning both semantic and motion patterns. For that, we reformulate the popular shuffling pretext task within a modern contrastive learning paradigm. We show that our transformer-based network has a natural capacity to learn motion in self-supervised settings and achieves strong performance, outperforming CVRL on four benchmarks.

关键词： Representation learning Visualization Semantics Self-supervised learning Benchmark testing Transformers pattern recognition

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Translation Symmetry Detection: A Repetitive pattern Analysis Approach

Translation Symmetry Detection: A Repetitive Pattern Analysi...

引用

26th ieee conference on computer vision and pattern recognition (CVPR)

作者： Cai, Yunliang Baciu, George Hong Kong Polytech Univ Dept Comp GAMA Lab Hong Kong Hong Kong Peoples R China

ISBN: (纸本)9780769549903

Translation symmetry is one of the most important pattern characteristics in natural and man-made environments. Detecting translation symmetry is a grand challenge in computer vision. This has a large spectrum of real-world applications from industrial settings to design, arts, entertainment and eduction. This paper describes the algorithm we have submitted for the Symmetry Detection Competition 2013. We introduce two new concepts in our symmetric repetitive pattern detection algorithm. The first concept is the bottom-up detection-inference approach. This extends the versatility of current detection methods to a higher level segmentation. The second concept is the framework of a new theoretical analysis of invariant repetitive patterns. This is crucial in symmetry/non-symmetry structure extraction but has less coverage in the previous literature on pattern detection and classification.

关键词： computer vision image segmentation pattern classification

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