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检索条件"任意字段=IEEE Conference on Computer Vision and Pattern Recognition"
53167 条 记 录,以下是4921-4930 订阅
Cross-Modal Center Loss for 3D Cross-Modal Retrieval
Cross-Modal Center Loss for 3D Cross-Modal Retrieval
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Jing, Longlong Vahdani, Elahe Tan, Jiaxing Tian, Yingli CUNY New York NY 10021 USA
Cross-modal retrieval aims to learn discriminative and modal-invariant features for data from different modalities. Unlike the existing methods which usually learn from the features extracted by offline networks, in t... 详细信息
来源: 评论
Glancing at the Patch: Anomaly Localization with Global and Local Feature Comparison
Glancing at the Patch: Anomaly Localization with Global and ...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Wang, Shenzhi Wu, Liwei Cui, Lei Shen, Yujun SenseTime Res Hong Kong Peoples R China Chinese Univ Hong Kong Hong Kong Peoples R China
Anomaly localization, with the purpose to segment the anomalous regions within images, is challenging due to the large variety of anomaly types. Existing methods typically train deep models by treating the entire imag... 详细信息
来源: 评论
Leveraging Multi scale Backbone with Multilevel supervision for Thermal Image Super Resolution
Leveraging Multi scale Backbone with Multilevel supervision ...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Nathan, Sabari Kansal, Priya Couger Inc Shibuya Ku Tokyo Japan
This paper proposes an attention-based multi-level model with a multi-scale backbone for thermal image super-resolution. The model leverages the multi-scale backbone as well. The thermal image dataset is provided by P... 详细信息
来源: 评论
Understanding the Robustness of 3D Object Detection with Bird'View Representations in Autonomous Driving
Understanding the Robustness of 3D Object Detection with Bir...
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2023 ieee/CVF conference on computer vision and pattern recognition, CVPR 2023
作者: Zhu, Zijian Zhang, Yichi Chen, Hai Dong, Yinpeng Zhao, Shu Ding, Wenbo Zhong, Jiachen Zheng, Shibao Institute of Image Communication and Network Engineering Shanghai Jiao Tong University China Institute for Ai Tsinghua University BNRist Center Thbi Lab Dept. of Comp. Sci. and Tech. China School of Computer Science and Technology Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Information Materials and Intelligent Sensing Laboratory of Anhui Province China Saic Motor Ai Lab Zhongguancun Laboratory China
3D object detection is an essential perception task in autonomous driving to understand the environments. The Bird's-Eye-View (BEV) representations have significantly improved the performance of 3D detectors with ... 详细信息
来源: 评论
Composing Photos Like a Photographer
Composing Photos Like a Photographer
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Hong, Chaoyi Du, Shuaiyuan Xian, Ke Lu, Hao Cao, Zhiguo Zhong, Weicai Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Minist Educ Key Lab Image Proc & Intelligent Control Wuhan Hubei Peoples R China Huawei CBG Consumer Cloud Serv Prod & Big Data Platform Dept Shenzhen Peoples R China
We show that explicit modeling of composition rules benefits image cropping. Image cropping is considered a promising way to automate aesthetic composition in professional photography. Existing efforts, however;only m... 详细信息
来源: 评论
Improving the Efficiency-Accuracy Trade-off of DETR-Style Models in Practice
Improving the Efficiency-Accuracy Trade-off of DETR-Style Mo...
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ieee computer Society conference on computer vision and pattern recognition Workshops (CVPRW)
作者: Yumin Suh Dongwan Kim Abhishek Aich Samuel Schulter Jong-Chyi-Su Bohyung Han Manmohan Chandraker NEC Laboratories America Seoul National University
We aim to provide a comprehensive view of the inference efficiency of DETR-style detection models. We explore the effect of basic efficiency techniques and identify the factors that are easy to implement, yet effectiv... 详细信息
来源: 评论
Jigsaw Clustering for Unsupervised Visual Representation Learning
Jigsaw Clustering for Unsupervised Visual Representation Lea...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Chen, Pengguang Liu, Shu Jia, Jiaya Chinese Univ Hong Kong Hong Kong Peoples R China SmartMore Hong Kong Peoples R China
Unsupervised representation learning with contrastive learning achieved great success. This line of methods duplicate each training batch to construct contrastive pairs, making each training batch and its augmented ve... 详细信息
来源: 评论
Virtual Fully-Connected Layer: Training a Large-Scale Face recognition Dataset with Limited Computational Resources
Virtual Fully-Connected Layer: Training a Large-Scale Face R...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Li, Pengyu Wang, Biao Zhang, Lei Alibaba Grp Artificial Intelligence Ctr DAMO Acad Hangzhou Peoples R China Hong Kong Polytech Univ Dept Comp Hong Kong Peoples R China
Recently, deep face recognition has achieved significant progress because of Convolutional Neural Networks (CNNs) and large-scale datasets. However, training CNNs on a large-scale face recognition dataset with limited... 详细信息
来源: 评论
Anchor-Free Person Search
Anchor-Free Person Search
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Yan, Yichao Li, Jinpeng Qin, Jie Bai, Song Liao, Shengcai Liu, Li Zhu, Fan Shao, Ling Incept Inst Artificial Intelligence IIAI Abu Dhabi U Arab Emirates Univ Oxford Oxford England
Person search aims to simultaneously localize and identify a query person from realistic, uncropped images, which can be regarded as the unified task of pedestrian detection and person re-identification (re-id). Most ... 详细信息
来源: 评论
Advanced Techniques for Chinese Image Captioning: Investigating Attention Mechanisms Based on Object Detection for Chinese Image Caption Generation  5
Advanced Techniques for Chinese Image Captioning: Investigat...
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5th International conference on Machine Learning and computer Application, ICMLCA 2024
作者: Hua, Yongbin Li, Pei'ang Zeng, Xiangjin Xu, Hong School of Computer Science and Engineering Wuhan Institute of Technology Hubei Wuhan China
The task of image caption generation aims to automatically produce natural language descriptions that match the content of images, integrating the fields of machine vision and natural language processing, which holds ... 详细信息
来源: 评论