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检索条件"任意字段=IEEE/CVF Conference on Computer Vision and Pattern Recognition"
23228 条 记 录,以下是4871-4880 订阅
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Hierarchical Video Prediction using Relational Layouts for Human-Object Interactions
Hierarchical Video Prediction using Relational Layouts for H...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Bodla, Navaneeth Shrivastava, Gaurav Chellappa, Rama Shrivastava, Abhinav Univ Maryland College Pk MD 20742 USA Johns Hopkins Univ Baltimore MD USA
Learning to model and predict how humans interact with objects while performing an action is challenging, and most of the existing video prediction models are ineffective in modeling complicated human-object interacti... 详细信息
来源: 评论
Towards Extremely Compact RNNs for Video recognition with Fully Decomposed Hierarchical Tucker Structure
Towards Extremely Compact RNNs for Video Recognition with Fu...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Yin, Miao Liao, Siyu Liu, Xiao-Yang Wang, Xiaodong Yuan, Bo Rutgers State Univ Newark NJ 07101 USA Amazon Seattle WA USA Columbia Univ New York NY 10027 USA
Recurrent Neural Networks (RNNs) have been widely used in sequence analysis and modeling. However, when processing high-dimensional data, RNNs typically require very large model sizes, thereby bringing a series of dep... 详细信息
来源: 评论
M3DSSD: Monocular 3D Single Stage Object Detector
M3DSSD: Monocular 3D Single Stage Object Detector
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Luo, Shujie Dai, Hang Shao, Ling Ding, Yong Zhejiang Univ Coll Informat Sci & Elect Engn Hangzhou Peoples R China Zhejiang Univ Sch Micronano Elect Hangzhou Peoples R China Mohamed Bin Zayed Univ Artificial Intelligence Abu Dhabi U Arab Emirates Incept Inst Artificial Intelligence Abu Dhabi U Arab Emirates
In this paper, we propose a Monocular 3D Single Stage object Detector (M3DSSD) with feature alignment and asymmetric non-local attention. Current anchor-based monocular 3D object detection methods suffer from feature ... 详细信息
来源: 评论
A Closer Look at Self-training for Zero-Label Semantic Segmentation
A Closer Look at Self-training for Zero-Label Semantic Segme...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Pastore, Giuseppe Cermelli, Fabio Xian, Yongqin Mancini, Massimiliano Akata, Zeynep Caputo, Barbara Politecn Torino Turin Italy Italian Inst Technol Genoa Italy MPI Informat Saarbrucken Germany Univ Tubingen Tubingen Germany MPI Intelligent Syst Saarbrucken Germany
Being able to segment unseen classes not observed during training is an important technical challenge in deep learning, because of its potential to reduce the expensive annotation required for semantic segmentation. P... 详细信息
来源: 评论
LAFEAT: Piercing Through Adversarial Defenses with Latent Features
LAFEAT: Piercing Through Adversarial Defenses with Latent Fe...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Yu, Yunrui Gao, Xitong Xu, Cheng-Zhong Univ Macau Macau Sar Peoples R China Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen Peoples R China
Deep convolutional neural networks are susceptible to adversarial attacks. They can be easily deceived to give an incorrect output by adding a tiny perturbation to the input. This presents a great challenge in making ... 详细信息
来源: 评论
ECKPN: Explicit Class Knowledge Propagation Network for Transductive Few-shot Learning
ECKPN: Explicit Class Knowledge Propagation Network for Tran...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Chen, Chaofan Yang, Xiaoshan Xu, Changsheng Huang, Xuhui Ma, Zhe Univ Sci & Technol China USTC Sch Informat Sci & Technol Hefei Anhui Peoples R China Chinese Acad Sci CASIA Inst Automat Natl Lab Pattern Recognit NLPR Beijing Peoples R China Univ Chinese Acad Sci UCAS Sch Artificial Intelligence Beijing Peoples R China Second Acad CASIC X Lab Beijing Peoples R China
Recently, the transductive graph-based methods have achieved great success in the few-shot classification task. However, most existing methods ignore exploring the class-level knowledge that can be easily learned by h... 详细信息
来源: 评论
Combining Semantic Guidance and Deep Reinforcement Learning For Generating Human Level Paintings
Combining Semantic Guidance and Deep Reinforcement Learning ...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Singh, Jaskirat Zheng, Liang Australian Natl Univ Canberra ACT Australia
Generation of stroke-based non-photorealistic imagery, is an important problem in the computer vision community. As an endeavor in this direction, substantial recent research efforts have been focused on teaching mach... 详细信息
来源: 评论
Generalized Foggy-Scene Semantic Segmentation by Frequency Decoupling
Generalized Foggy-Scene Semantic Segmentation by Frequency D...
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ieee computer Society conference on computer vision and pattern recognition Workshops (CVPRW)
作者: Qi Bi Shaodi You Theo Gevers Computer Vision Research Group University of Amsterdam Amsterdam The Netherlands
Foggy-scene semantic segmentation (FSSS) is highly challenging due to the diverse effects of fog on scene properties and the limited training data. Existing research has mainly focused on domain adaptation for FSSS, w... 详细信息
来源: 评论
Difficulty Estimation with Action Scores for computer vision Tasks
Difficulty Estimation with Action Scores for Computer Vision...
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ieee computer Society conference on computer vision and pattern recognition Workshops (CVPRW)
作者: Octavio Arriaga Sebastian Palacio Matias Valdenegro-Toro University of Bremen German Research Center for Artificial Intelligence University of Groningen
As more machine learning models are now being applied in real world scenarios it has become crucial to evaluate their difficulties and biases. In this paper we present an unsupervised method for calculating a difficul...
来源: 评论
Enriching ImageNet with Human Similarity Judgments and Psychological Embeddings
Enriching ImageNet with Human Similarity Judgments and Psych...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Roads, Brett D. Love, Bradley C. UCL Dept Expt Psychol London England
Advances in supervised learning approaches to object recognition flourished in part because of the availability of high-quality datasets and associated benchmarks. However, these benchmarks-such as ILSVRC-are relative... 详细信息
来源: 评论