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Understanding Objects in Detail with Fine-Grained Attributes

Andrea Vedaldi, Siddharth Mahendran, Stavros Tsogkas, Subhransu Maji, Ross Girshick, Juho Kannala, Esa Rahtu, Iasonas Kokkinos, Matthew B. Blaschko, David Weiss, Ben Taskar, Karen Simonyan (+2 others)
2014 2014 IEEE Conference on Computer Vision and Pattern Recognition  
We study the problem of understanding objects in detail, intended as recognizing a wide array of fine-grained object attributes.  ...  To this end, we introduce a dataset of 7,413 airplanes annotated in detail with parts and their attributes, leveraging images donated by airplane spotters and crowdsourcing both the design and collection  ...  All the images in our dataset were kindly provided by Mick Bajcar, who very generously agreed to allow the community to use his images exclusively for non-commercial research purposes, provided that a  ... 
doi:10.1109/cvpr.2014.463 dblp:conf/cvpr/VedaldiMTMGKRKBWTSSM14 fatcat:n2bzqoqnb5binpie7nrzctozcy

Sequential Dual Attention: Coarse-to-Fine-Grained Hierarchical Generation for Image Captioning

Zhibin Guan, Kang Liu, Yan Ma, Xu Qian, Tongkai Ji
2018 Symmetry  
The existing image captioning methods rarely consider generating a final description sentence in a coarse-grained to fine-grained way, which is how humans understand the surrounding scenes; and the generated  ...  The advantage of our SDA-CFGHG method is that it can achieve image captioning in a coarse-to-fine-grained way and the generated textual sentence can capture details of the raw image to some degree.  ...  Finally, the object features are combined with the attribute features to generate final fine-grained information set, denoted as V (see Equation (5) ): V = {v 1 , v 2 , ..., v Q+Z }, v j ∈ R 2048 , j  ... 
doi:10.3390/sym10110626 fatcat:akzzyoacpfamjjuacdbfx3t5ii

Exploring Semantic Relationships for Unpaired Image Captioning [article]

Fenglin Liu, Meng Gao, Tianhao Zhang, Yuexian Zou
2021 arXiv   pre-print
In addition, even for the most advanced image captioning systems, it is still difficult to realize deep image understanding.  ...  In this work, we achieve unpaired image captioning by bridging the vision and the language domains with high-level semantic information.  ...  The w/ Object has more objects but lacks details, e.g. color and number. The w/ Attribute generates more detailed attributes and color.  ... 
arXiv:2106.10658v2 fatcat:hlbpc4oz3nft3h26zqwyxi5dyu

A Massive Image Recognition Algorithm Based on Attribute Modelling and Knowledge Acquisition

Guohua Li, An Liu, Huajie Shen, Miaochao Chen
2021 Advances in Mathematical Physics  
implied by all the present attribute values in incomplete data.  ...  missing attribute as output alone and other attributes as input in turn, and the network structure can deeply portray the association relationships between each attribute and other attributes.  ...  for fine-grained visual understanding tasks.  ... 
doi:10.1155/2021/4632070 fatcat:ff2c5fmiovgczpe6kwbi5nnoda

Fine-grained sketch-based image retrieval: The role of part-aware attributes

Ke Li, Kaiyue Pang, Yi-Zhe Song, Timothy Hospedales, Honggang Zhang, Yichuan Hu
2016 2016 IEEE Winter Conference on Applications of Computer Vision (WACV)  
To address this, we propose to detect visual attributes at part-level, in order to build a new representation that not only captures fine-grained characteristics but also traverses across visual domains  ...  We study the problem of fine-grained sketch-based image retrieval.  ...  Attributes capture information beyond the standard phraseology of object categories, instances, and parts, where finegrained attributes further describe object parts with more detail.  ... 
doi:10.1109/wacv.2016.7477615 dblp:conf/wacv/LiPSHZH16 fatcat:7jcxle5e45dbrei6p6yeyr7x7e

Fashionpedia: Ontology, Segmentation, and an Attribute Localization Dataset [article]

Menglin Jia, Mengyun Shi, Mikhail Sirotenko, Yin Cui, Claire Cardie, Bharath Hariharan, Hartwig Adam, Serge Belongie
2020 arXiv   pre-print
In this work we explore the task of instance segmentation with attribute localization, which unifies instance segmentation (detect and segment each object instance) and fine-grained visual attribute categorization  ...  with everyday and celebrity event fashion images annotated with segmentation masks and their associated per-mask fine-grained attributes, built upon the Fashionpedia ontology.  ...  We also thank Zeqi Gu, Fisher Yu, Wenqi Xian, Chao Suo, Junwen Bai, Paul Upchurch, Anmol Kabra, and Brendan Rappazzo for their help developing the fine-grained attribute annotation tool.  ... 
arXiv:2004.12276v2 fatcat:b7xvkqcxuncxhe3bybuwllqn2a

Classifying Object Manipulation Actions based on Grasp-types and Motion-Constraints [article]

Kartik Gupta, Darius Burschka, Arnav Bhavsar
2018 arXiv   pre-print
In this work, we address a challenging problem of fine-grained and coarse-grained recognition of object manipulation actions.  ...  Our results justifies the efficacy of grasp attributes for the task of fine-grained and coarse-grained object manipulation action recognition.  ...  Also, we perform fine-grained action recognition based on fine-grained grasp attributes.  ... 
arXiv:1806.07574v1 fatcat:4vtq63rgxbbkjlr5zbalw2oufe

Synergistic Instance-Level Subspace Alignment for Fine-Grained Sketch-Based Image Retrieval

Ke Li, Kaiyue Pang, Yi-Zhe Song, Timothy M. Hospedales, Tao Xiang, Honggang Zhang
2017 IEEE Transactions on Image Processing  
We study the problem of fine-grained sketch-based image retrieval.  ...  in two different visual domains, i.e. black and white lines vs. color pixels, and (iii) fine-grained distinctions are especially challenging when executed across domain and abstraction-level.  ...  Attributes capture information beyond the standard phraseology of object categories, instances, and parts, where fine-grained attributes further describe object parts with more detail.  ... 
doi:10.1109/tip.2017.2745106 pmid:28858796 fatcat:dhp2a73iyvg67kk7yu5z2x6u7m

Attend and Interact: Higher-Order Object Interactions for Video Understanding

Chih-Yao Ma, Asim Kadav, Iain Melvin, Zsolt Kira, Ghassan AlRegib, Hans Peter Graf
2018 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition  
In this paper, we propose to efficiently learn higher-order interactions between arbitrary subgroups of objects for fine-grained video understanding.  ...  However, existing approaches to fine-grained video understanding or visual relationship detection often rely on single object representation or pairwise object relationships.  ...  This indicates that the top 15 objects with highest ROI score are sufficient to represent fine-grained details of the video.  ... 
doi:10.1109/cvpr.2018.00710 dblp:conf/cvpr/MaKMKAG18 fatcat:k6cmthc3tjgr7o2dusljnpdeay

Fine-Grained Identification of Clothing Apparels

Kushal Kothari, Ajay Arjunwadkar, Hitesh Bhalerao, Savita Lade
2022 International Journal for Research in Applied Science and Engineering Technology  
Analyzing fashion attributes is also crucial in the fashion design process.  ...  Keywords: Computer Vision, Fine grained identification, Clothing apparel detection, Convolutional Neural Network, Mask RCNN, Detectron2  ...  PROPOSED SYSTEM Here, the fundamental task is instance segmentation with attribute localization, which unifies instance segmentation (detect and segment each object instance) and fine-grained visual attribute  ... 
doi:10.22214/ijraset.2022.42022 fatcat:k6oam4qdrja37mgitlhm6klkbq

Fine-Grained Object Recognition and Zero-Shot Learning in Remote Sensing Imagery

Gencer Sumbul, Ramazan Gokberk Cinbis, Selim Aksoy
2018 IEEE Transactions on Geoscience and Remote Sensing  
Fine-grained object recognition that aims to identify the type of an object among a large number of subcategories is an emerging application with the increasing resolution that exposes new details in image  ...  We introduce a new data set that contains 40 different types of street trees in 1-ft spatial resolution aerial data, and evaluate the performance of this model with manually annotated attributes, a natural  ...  We use different splits of this imbalanced data set for a fair and objective evaluation of fine-grained object recognition with ZSL as suggested in [16] and presented in Section IV.  ... 
doi:10.1109/tgrs.2017.2754648 fatcat:cgjm42zdovcbnc57cjt7rki4dm

Knowledge-Embedded Representation Learning for Fine-Grained Image Recognition

Tianshui Chen, Liang Lin, Riquan Chen, Yang Wu, Xiaonan Luo
2018 Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence  
Humans can naturally understand an image in depth with the aid of rich knowledge accumulated from daily lives or professions.  ...  of fine-grained image recognition.  ...  Humans can naturally understand an image in depth with the aid of rich knowledge accumulated from daily lives or professions.  ... 
doi:10.24963/ijcai.2018/87 dblp:conf/ijcai/ChenLCWL18 fatcat:iek67dt6mzftld5cll247t6mfa

Part-Stacked CNN for Fine-Grained Visual Categorization

Shaoli Huang, Zhe Xu, Dacheng Tao, Ya Zhang
2016 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)  
In the context of fine-grained visual categorization, the ability to interpret models as human-understandable visual manuals is sometimes as important as achieving high classification accuracy.  ...  In this paper, we propose a novel Part-Stacked CNN architecture that explicitly explains the finegrained recognition process by modeling subtle differences from object parts.  ...  " on how to distinguish fine-grained categories in detail.  ... 
doi:10.1109/cvpr.2016.132 dblp:conf/cvpr/HuangXTZ16 fatcat:bc2zb23bpzbhrf3wq47r5mtlha

Embedding Label Structures for Fine-Grained Feature Representation

Xiaofan Zhang, Feng Zhou, Yuanqing Lin, Shaoting Zhang
2016 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)  
Understanding objects in detail with fine-grained at- tributes. In CVPR, pages 3622–3629. IEEE, 2014. 3 [38] C. Wah, G. Van Horn, S. Branson, S. Maji, P. Perona, and S. Belongie.  ...  Deformable part descriptors for fine-grained recognition and attribute prediction. In ICCV, pages 729–736.  ... 
doi:10.1109/cvpr.2016.126 dblp:conf/cvpr/ZhangZLZ16 fatcat:aa5v7iwcwbaphhxkjrp2qypoje

Part-Stacked CNN for Fine-Grained Visual Categorization [article]

Shaoli Huang, Zhe Xu,Dacheng Tao,Ya Zhang
2015 arXiv   pre-print
In the context of fine-grained visual categorization, the ability to interpret models as human-understandable visual manuals is sometimes as important as achieving high classification accuracy.  ...  In this paper, we propose a novel Part-Stacked CNN architecture that explicitly explains the fine-grained recognition process by modeling subtle differences from object parts.  ...  overlooked, i.e., the ability to generate a human-understandable "manual" on how to distinguish fine-grained categories in detail.  ... 
arXiv:1512.08086v1 fatcat:f5n6un6jw5gznjqcrrsctjzxhi
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