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检索条件"任意字段=2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2020"
11281 条 记 录,以下是601-610 订阅
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Semi-supervised Parametric Real-world Image Harmonization
Semi-supervised Parametric Real-world Image Harmonization
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Wang, Ke Gharbi, Michael Zhang, He Xia, Zhihao Shechtman, Eli Adobe Inc San Jose CA 95110 USA Univ Calif Berkeley EECS Berkeley CA 94720 USA
Learning-based image harmonization techniques are usually trained to undo synthetic random global transformations applied to a masked foreground in a single ground truth photo. This simulated data does not model many ... 详细信息
来源: 评论
Improving Visual Grounding by Encouraging Consistent Gradient-based Explanations
Improving Visual Grounding by Encouraging Consistent Gradien...
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Yang, Ziyan Kafle, Kushal Dernoncourt, Franck Ordonez, Vicente Rice Univ Houston TX 77005 USA Adobe Res San Francisco CA USA
We propose a margin-based loss for tuning joint vision-language models so that their gradient-based explanations are consistent with region-level annotations provided by humans for relatively smaller grounding dataset... 详细信息
来源: 评论
Neural Dependencies Emerging from Learning Massive Categories
Neural Dependencies Emerging from Learning Massive Categorie...
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Feng, Ruili Zheng, Kecheng Zhu, Kai Shen, Yujun Zhao, Jian Huang, Yukun Zhao, Deli Zhou, Jingren Jordan, Michael Zha, Zheng-Jun Univ Sci & Technol China Hefei Peoples R China Ant Grp Hangzhou Peoples R China Alibaba Grp Hangzhou Peoples R China Univ Calif Berkeley Berkeley CA USA
This work presents two astonishing findings on neural networks learned for large-scale image classification. 1) Given a well-trained model, the logits predicted for some category can be directly obtained by linearly c... 详细信息
来源: 评论
Model-Agnostic Gender Debiased Image Captioning
Model-Agnostic Gender Debiased Image Captioning
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Hirota, Yusuke Nakashima, Yuta Garcia, Noa Osaka Univ Suita Osaka 565 Japan
Image captioning models are known to perpetuate and amplify harmful societal bias in the training set. In this work, we aim to mitigate such gender bias in image captioning models. While prior work has addressed this ... 详细信息
来源: 评论
Multi-modal In-Context Learning Makes an Ego-evolving Scene Text Recognizer
Multi-modal In-Context Learning Makes an Ego-evolving Scene ...
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Zhao, Zhen Tang, Jingqun Lin, Chunhui Wu, Binghong Huang, Can Liu, Hao Tan, Xin Zhang, Zhizhong Xie, Yuan East China Normal Univ Shanghai Peoples R China ByteDance Beijing Peoples R China
Scene text recognition (STR) in the wild frequently encounters challenges when coping with domain variations, font diversity, shape deformations, etc. A straight-forward solution is performing model fine-tuning tailor... 详细信息
来源: 评论
Logical Implications for Visual Question Answering Consistency
Logical Implications for Visual Question Answering Consisten...
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Tascon-Morales, Sergio Marquez-Neila, Pablo Sznitman, Raphael Univ Bern Bern Switzerland
Despite considerable recent progress in Visual Question Answering (VQA) models, inconsistent or contradictory answers continue to cast doubt on their true reasoning capabilities. However, most proposed methods use ind... 详细信息
来源: 评论
Visual recognition by Request
Visual Recognition by Request
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Tang, Chufeng Xie, Lingxi Zhang, Xiaopeng Hu, Xiaolin Tian, Qi Tsinghua Univ Dept Comp Sci & Technol Beijing Peoples R China Huawei Inc Montreal PQ Canada Chinese Inst Brain Res CIBR Beijing Peoples R China Tsinghua Univ THBI McGovern Inst Brain Res IDGR Beijing Peoples R China
Humans have the ability of recognizing visual semantics in an unlimited granularity, but existing visual recognition algorithms cannot achieve this goal. In this paper, we establish a new paradigm named visual recogni... 详细信息
来源: 评论
DELTA: Decoupling Long-Tailed Online Continual Learning
DELTA: Decoupling Long-Tailed Online Continual Learning
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Raghavan, Siddeshwar He, Jiangpeng Zhu, Fengqing Purdue Univ Sch Elect & Comp Engn W Lafayette IN 47907 USA
A significant challenge in achieving ubiquitous Artificial Intelligence is the limited ability of models to rapidly learn new information in real-world scenarios where data follows long-tailed distributions, all while... 详细信息
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Graph Representation for Order-aware Visual Transformation
Graph Representation for Order-aware Visual Transformation
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Qiu, Yue Sun, Yanjun Matsuzawa, Fumiya Iwata, Kenji Kataoka, Hirokatsu Natl Inst Adv Ind Sci & Technol Tokyo Japan
This paper proposes a new visual reasoning formulation that aims at discovering changes between image pairs and their temporal orders. Recognizing scene dynamics and their chronological orders is a fundamental aspect ... 详细信息
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ANIM: Accurate Neural Implicit Model for Human Reconstruction from a single RGB-D image
ANIM: Accurate Neural Implicit Model for Human Reconstructio...
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Pesavento, Marco Xu, Yuanlu Sarafianos, Nikolaos Maier, Robert Wang, Ziyan Yao, Chun-Han Volino, Marco Boyer, Edmond Hilton, Adrian Tung, Tony Univ Surrey CVSSP Guildford Surrey England UC Merced Merced CA USA Meta Real Labs Sausalito CA USA
Recent progress in human shape learning, shows that neural implicit models are effective in generating 3D human surfaces from limited number of views, and even from a single RGB image. However, existing monocular appr... 详细信息
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