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检索条件"任意字段=2006 Conference on Computer Vision and Pattern Recognition Workshops"
5506 条 记 录,以下是341-350 订阅
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When NAS Meets Trees: An Efficient Algorithm for Neural Architecture Search
When NAS Meets Trees: An Efficient Algorithm for Neural Arch...
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Qian, Guocheng Zhang, Xuanyang Li, Guohao Zhao, Chen Chen, Yukang Zhang, Xiangyu Ghanem, Bernard Sun, Jian King Abdullah Univ Sci & Technol KAUST Thuwal Saudi Arabia MEGVII Technol Beijing Peoples R China Chinese Univ Hong Kong Hong Kong Peoples R China
The key challenge in neural architecture search (NAS) is designing how to explore wisely in the huge search space. We propose a new NAS method called TNAS (NAS with trees), which improves search efficiency by explorin... 详细信息
来源: 评论
Multi-task Learning with Attention for End-to-end Autonomous Driving
Multi-task Learning with Attention for End-to-end Autonomous...
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Ishihara, Keishi Kanervisto, Anssi Miura, Jun Hautamaki, Ville Toyohashi Univ Technol Toyohashi Aichi Japan Univ Eastern Finland Kuopio Finland
Autonomous driving systems need to handle complex scenarios such as lane following, avoiding collisions, taking turns, and responding to traffic signals. In recent years, approaches based on end-to-end behavioral clon... 详细信息
来源: 评论
Self-supervised vision Transformers for Land-cover Segmentation and Classification
Self-supervised Vision Transformers for Land-cover Segmentat...
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Scheibenreif, Linus Hanna, Joelle Mommert, Michael Borth, Damian Univ St Gallen AIML Lab Sch Comp Sci Rosenbergstr 30 St Gallen Switzerland
Transformer models have recently approached or even surpassed the performance of ConvNets on computer vision tasks like classification and segmentation. To a large degree, these successes have been enabled by the use ... 详细信息
来源: 评论
Deep Learning based Spatial-Temporal In-loop filtering for Versatile Video Coding
Deep Learning based Spatial-Temporal In-loop filtering for V...
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Pham, Chi D. K. Fu, Chen Zhou, Jinjia Hosei Univ Tokyo Japan JST PRESTO Saitama Japan
The existing deep learning-based Versatile Video Coding (VVC) in-loop filtering (ILF) enhancement works mainly focus on learning the one-to-one mapping between the reconstructed and the original video frame, ignoring ... 详细信息
来源: 评论
Towards Semantic Understanding of Surrounding Vehicular Maneuvers: A Panoramic vision-Based Framework for Real-World Highway Studies  29
Towards Semantic Understanding of Surrounding Vehicular Mane...
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29th IEEE conference on computer vision and pattern recognition (CVPR)
作者: Kristoffersen, Miklas S. Dueholm, Jacob V. Satzoda, Ravi K. Trivedi, Mohan M. Mogelmose, Andreas Moeslund, Thomas B. Univ Calif San Diego San Diego CA 92103 USA Aalborg Univ Aalborg Denmark
This paper proposes the use of multiple low-cost visual sensors to obtain a surround view of the ego-vehicle for semantic understanding. A multi-perspective view will assist the analysis of naturalistic driving studie... 详细信息
来源: 评论
Out-Of-Distribution Detection In Unsupervised Continual Learning
Out-Of-Distribution Detection In Unsupervised Continual Lear...
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: He, Jiangpeng Zhu, Fengqing Purdue Univ Elmore Family Sch Elect & Comp Engn W Lafayette IN 47907 USA
Unsupervised continual learning aims to learn new tasks incrementally without requiring human annotations. However, most existing methods, especially those targeted on image classification, only work in a simplified s... 详细信息
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Disentangled Loss for Low-Bit Quantization-Aware Training
Disentangled Loss for Low-Bit Quantization-Aware Training
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Allenet, Thibault Briand, David Bichler, Olivier Sentieys, Olivier CEA LIST Saclay France Univ Rennes INRIA Rennes France
Quantization-Aware Training (QAT) has recently showed a lot of potential for low-bit settings in the context of image classification. Approaches based on QAT are using the Cross Entropy Loss function which is the refe... 详细信息
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MIPI 2024 Challenge on Nighttime Flare Removal: Methods and Results
MIPI 2024 Challenge on Nighttime Flare Removal: Methods and ...
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Dai, Yuekun Zhang, Dafeng Li, Xiaoming Yue, Zongsheng Li, Chongyi Zhou, Shangchen Feng, Ruicheng Yang, Peiqing Jin, Zhezhu Liu, Guanqun Loy, Chen Change Nanyang Technol Univ S Lab Singapore Singapore Samsung Res China Nanjing Peoples R China Nankai Univ Tianjin Peoples R China
The increasing demand for computational photography and imaging on mobile platforms has led to the widespread development and integration of advanced image sensors with novel algorithms in camera systems. However, the... 详细信息
来源: 评论
Super-Resolution based Video Coding Scheme
Super-Resolution based Video Coding Scheme
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Cho, Hyun Min Choi, Kiho Gacheon Univ Sch Comp 1342 Seongnamdaero Seongnam Si Gyeonggi Do South Korea
In this paper, we present a super-resolution-based video coding scheme that compresses video data by combining traditional hybrid video coding and Convolutional neural network-based video coding. During video encoding... 详细信息
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CorrGAN: Input Transformation Technique Against Natural Corruptions
CorrGAN: Input Transformation Technique Against Natural Corr...
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Haque, Mirazul Budnik, Christof J. Yang, Wei UT Dallas Richardson TX 75080 USA Siemens Corp Technol Princeton NJ USA
Because of the increasing accuracy of Deep Neural Networks (DNNs) on different tasks, a lot of real times systems are utilizing DNNs. These DNNs are vulnerable to adversarial perturbations and corruptions. Specificall... 详细信息
来源: 评论