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检索条件"任意字段=IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops"
12859 条 记 录,以下是111-120 订阅
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Self Texture Transfer Networks for Low Bitrate Image Compression
Self Texture Transfer Networks for Low Bitrate Image Compres...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Iwai, Shoma Miyazaki, Tomo Sugaya, Yoshihiro Omachi, Shinichiro Tohoku Univ Grad Sch Engn Dept Commun Sendai Miyagi Japan
Lossy image compression causes a loss of texture, especially at low bitrate. To mitigate this problem, we propose a novel image compression method that utilizes a reference-based image super-resolution model. We use t... 详细信息
来源: 评论
Robust and Online Vehicle Counting at Crowded Intersections
Robust and Online Vehicle Counting at Crowded Intersections
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Lu, Jincheng Xia, Meng Gao, Xu Yang, Xipeng Tao, Tianran Meng, Hao Zhang, Wei Tan, Xiao Shi, Yifeng Li, Guanbin Ding, Errui
In this paper, we propose an online movement-specific vehicle counting system to realize robust traffic flow analysis at crowded intersections. Our proposed framework adopts PP-YOLO as the vehicle detector and adapts ... 详细信息
来源: 评论
Towards Domain-Specific Explainable AI: Model Interpretation of a Skin Image Classifier using a Human Approach
Towards Domain-Specific Explainable AI: Model Interpretation...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Stieler, Fabian Rabe, Fabian Bauer, Bernhard Univ Augsburg Augsburg Germany
Machine Learning models have started to outperform medical experts in some classification tasks. Meanwhile, the question of how these classifiers produce certain results is attracting increasing research attention. Cu... 详细信息
来源: 评论
Robustness and Adaptation to Hidden Factors of Variation
Robustness and Adaptation to Hidden Factors of Variation
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Paul, William Burlina, Philippe Johns Hopkins Univ Appl Phys Lab Laurel MD 20723 USA
We tackle here a specific, still not widely addressed aspect, of AI robustness, which consists of seeking invariance / insensitivity of model performance to hidden factors of variations in the data. Towards this end, ... 详细信息
来源: 评论
Designing a Moral Compass for the Future of computer vision using Speculative Analysis  30
Designing a Moral Compass for the Future of Computer Vision ...
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30th ieee/cvf conference on computer vision and pattern recognition workshops (CVPRW)
作者: Skirpan, Michael Yeh, Tom Univ Colorado Boulder CO 80309 USA
In this paper we discuss and analyze possible futures for technologies in the field of computer vision (CV). Using a method we have coined speculative analysis we take a broad look at research trends in the field to c... 详细信息
来源: 评论
MV-TAL: Mulit-view Temporal Action Localization in Naturalistic Driving
MV-TAL: Mulit-view Temporal Action Localization in Naturalis...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Li, Wei Chen, Shimin Gu, Jianyang Wang, Ning Chen, Chen Guo, Yandong OPPO Res Inst Beijing Peoples R China Zhejiang Univ Hangzhou Peoples R China East China Univ Sci & Technol Shanghai Peoples R China
Human risky behavior in driving is an important visual recognition problem. In this paper, we propose a multi-view temporal action localization system based on the grayscale video to achieve action recognition in natu... 详细信息
来源: 评论
Scalable and Explainable Outfit Generation
Scalable and Explainable Outfit Generation
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Lorbert, Alexander Neiman, David Poznanski, Arik Oks, Eduard Davis, Larry Amazon Seattle WA 98109 USA
We present an end-to-end system for learning outfit recommendations. The core problem we address is how a customer can receive clothing/accessory recommendations based on a current outfit and what type of item the cus... 详细信息
来源: 评论
Revisiting The Evaluation of Class Activation Mapping for Explainability: A Novel Metric and Experimental Analysis
Revisiting The Evaluation of Class Activation Mapping for Ex...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Poppi, Samuele Cornia, Marcella Baraldi, Lorenzo Cucchiara, Rita Univ Modena & Reggio Emilia Modena Italy
As the request for deep learning solutions increases, the need for explainability is even more fundamental. In this setting, particular attention has been given to visualization techniques, that try to attribute the r... 详细信息
来源: 评论
Can domain adaptation make object recognition work for everyone?
Can domain adaptation make object recognition work for every...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Prabhu, Viraj Selvaraju, Ramprasaath R. Hoffman, Judy Naik, Nikhil Georgia Tech Atlanta GA 30332 USA Artera AI Berkeley CA USA Salesforce Res Washington DC USA
Despite the rapid progress in deep visual recognition, modern computer vision datasets significantly overrepresent the developed world and models trained on such datasets underperform on images from unseen geographies... 详细信息
来源: 评论
Rank in Style: A Ranking-based Approach to Find Interpretable Directions
Rank in Style: A Ranking-based Approach to Find Interpretabl...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Kocasari, Umut Zaman, Kerem Tiftikci, Mert Simsar, Enis Yanardag, Pinar Bogazici Univ Istanbul Turkey TUM Munich Germany
Recent work such as StyleCLIP aims to harness the power of CLIP embeddings for controlled manipulations. Although these models are capable of manipulating images based on a text prompt, the success of the manipulation... 详细信息
来源: 评论