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检索条件"任意字段=IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops"
8966 条 记 录,以下是1171-1180 订阅
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Self-supervised multi-image super-resolution for push-frame satellite images
Self-supervised multi-image super-resolution for push-frame ...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Ngoc Long Nguyen Anger, Jeremy Davy, Axel Arias, Pablo Facciolo, Gabriele Univ Paris Saclay Ctr Borelli ENS Paris Saclay CNRS Gif Sur Yvette France Kayrros SAS Paris France
Recent constellations of optical satellites are adopting multi-image super-resolution (MISR) from bursts of push-frame images as a way to increase the resolution and reduce the noise of their products while maintainin... 详细信息
来源: 评论
ieee computer society
IEEE Computer Society
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ieee Winter Applications and computer vision workshops (WACVW)
ieee computer society
来源: 评论
Content-aware Input Scaling and Deep Learning Computation Offloading for Low-Latency Embedded vision
Content-aware Input Scaling and Deep Learning Computation Of...
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ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)
作者: Omkar Prabhune Tianen Chen Younghyun Kim Purdue University University of Wisconsin-Madison
Deploying deep learning (DL) models for visual recognition on embedded systems is often constrained by their limited compute power and storage capacity, and has stringent latency and power requirements. As emerging DL... 详细信息
来源: 评论
Sharpness-Aware Optimization for Real-World Adversarial Attacks for Diverse Compute Platforms with Enhanced Transferability
Sharpness-Aware Optimization for Real-World Adversarial Atta...
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ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)
作者: Muchao Ye Xiang Xu Qin Zhang Jonathan Wu Amazon AI Labs Seattle WA USA
In recent years, deep neural networks (DNNs) have become integral to many real-world applications. A pressing concern in these deployments pertains to their vulnerability to adversarial attacks. In this work, we focus... 详细信息
来源: 评论
Fast Camera Image Denoising on Mobile GPUs with Deep Learning, Mobile AI 2021 Challenge: Report
Fast Camera Image Denoising on Mobile GPUs with Deep Learnin...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Ignatov, Andrey Byeoung-Su, Kim Timofte, Radu Pouget, Angeline Song, Fenglong Li, Cheng Xiao, Shuai Fu, Zhongqian Maggioni, Matteo Huang, Yibin Cheng, Shen Lu, Xin Zhou, Yifeng Chen, Liangyu Liu, Donghao Zhang, Xiangyu Fan, Haoqiang Sun, Jian Liu, Shuaicheng Kwon, Minsu Lee, Myungje Yoo, Jaeyoon Kang, Changbeom Wang, Shinjo Huang, Bin Zhou, Tianbao Liu, Shuai Lei, Lei Feng, Chaoyu Huang, Liguang Lei, Zhikun Chen, Feifei Swiss Fed Inst Technol Comp Vis Lab Zurich Switzerland Samsung Elect Suwon South Korea AI Witchlabs Zollikerberg Switzerland Huawei Noahs Ark Lab Hong Kong Peoples R China Megvii Beijing Peoples R China ENERZAi Seoul South Korea Xiaomi AI Lab Beijing Peoples R China North China Univ Technol Beijing Peoples R China Xiaomi Inc Beijing Peoples R China Goodix Technol Algorithm Dept Shenzhen Peoples R China
Image denoising is one of the most critical problems in mobile photo processing. While many solutions have been proposed for this task, they are usually working with synthetic data and are too computationally expensiv... 详细信息
来源: 评论
Robust Automatic Motorcycle Helmet Violation Detection for an Intelligent Transportation System
Robust Automatic Motorcycle Helmet Violation Detection for a...
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ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)
作者: Duong Nguyen-Ngoc Tran Long Hoang Pham Hyung-Joon Jeon Huy-Hung Nguyen Hyung-Min Jeon Tai Huu-Phuong Tran Jae Wook Jeon Department of Electrical and Computer Engineering Sungkyunkwan University Suwon South Korea
Video surveillance-based automatic detection of motorcycle helmet usage can enhance the effectiveness of educational and enforcement initiatives aimed at boosting road safety. Current detection methods, however, have ...
来源: 评论
Simulating Task-Free Continual Learning Streams From Existing Datasets
Simulating Task-Free Continual Learning Streams From Existin...
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ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)
作者: Aristotelis Chrysakis Marie-Francine Moens Department of Computer Science KU Leuven Leuven Belgium
Task-free continual learning is the subfield of machine learning that focuses on learning online from a stream whose distribution changes continuously over time. In contrast, previous works evaluate task-free continua...
来源: 评论
Learnable Prompt for Few-Shot Semantic Segmentation in Remote Sensing Domain
Learnable Prompt for Few-Shot Semantic Segmentation in Remot...
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ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)
作者: Steve Andreas Immanuel Hagai Raja Sinulingga TelePIX Seoul South Korea
Few-shot segmentation is a task to segment objects or regions of novel classes within an image given only a few annotated examples. In the generalized setting, the task extends to segment both the base and the novel c... 详细信息
来源: 评论
Learning Optimized Low-Light Image Enhancement for Edge vision Tasks
Learning Optimized Low-Light Image Enhancement for Edge Visi...
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ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)
作者: S M A Sharif Azamat Myrzabekov Nodirkhuja Khujaev Roman Tsoy Seongwan Kim Jaeho Lee Opt-AI Inc. LG Sciencepark Seoul South Korea
Low-light image enhancement (LLIE) has a significant role in edge vision applications (EVA). Despite its widespread practicability, the existing LLIE methods are impractical due to their high computational costs. This... 详细信息
来源: 评论
Exploring the Impact of Dataset Bias on Dataset Distillation
Exploring the Impact of Dataset Bias on Dataset Distillation
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ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)
作者: Yao Lu Jianyang Gu Xuguang Chen Saeed Vahidian Qi Xuan Zhejiang University of Technology Zhejiang University Duke University
Dataset Distillation (DD) is a promising technique to synthesize a smaller dataset that preserves essential information from the original dataset. This synthetic dataset can serve as a substitute for the original larg... 详细信息
来源: 评论