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检索条件"任意字段=2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005"
6545 条 记 录,以下是201-210 订阅
排序:
OutfitGAN: Learning Compatible Items for Generative Fashion Outfits
OutfitGAN: Learning Compatible Items for Generative Fashion ...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Moosaei, Maryam Lin, Yusan Akhazhanov, Ablaikhan Chen, Huiyuan Wang, Fei Yang, Hao Visa Res San Francisco CA 94158 USA Univ Calif Los Angeles Los Angeles CA 90024 USA Nazarbayev Univ Astana Kazakhstan
Fashion-on-demand is becoming an important concept for fashion industries. Many attempts have been made to leverage machine learning methods to generate fashion designs tailored to customers' tastes. However, how ... 详细信息
来源: 评论
Key Point-Based Driver Activity recognition
Key Point-Based Driver Activity Recognition
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Vats, Arpita Anastasiu, David C. Santa Clara Univ Santa Clara CA 95053 USA
We present a key point-based activity recognition framework, built upon pre-trained human pose estimation and facial feature detection models. Our method extracts complex static and movement-based features from key fr... 详细信息
来源: 评论
Compositional Mixture Representations for vision and Text
Compositional Mixture Representations for Vision and Text
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Alaniz, Stephan Federici, Marco Akata, Zeynep Univ Tubingen Tubingen Germany Max Planck Inst Informat Saarbrucken Germany Univ Amsterdam Amsterdam Netherlands
Learning a common representation space between vision and language allows deep networks to relate objects in the image to the corresponding semantic meaning. We present a model that learns a shared Gaussian mixture re... 详细信息
来源: 评论
Anomaly Detection in Autonomous Driving: A Survey
Anomaly Detection in Autonomous Driving: A Survey
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Bogdoll, Daniel Nitsche, Maximilian Zoellner, J. Marius FZI Res Ctr Informat Technol Karlsruhe Germany KIT Karlsruhe Inst Technol Karlsruhe Germany
Nowadays, there are outstanding strides towards a future with autonomous vehicles on our roads. While the perception of autonomous vehicles performs well under closed-set conditions, they still struggle to handle the ... 详细信息
来源: 评论
Can domain adaptation make object recognition work for everyone?
Can domain adaptation make object recognition work for every...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Prabhu, Viraj Selvaraju, Ramprasaath R. Hoffman, Judy Naik, Nikhil Georgia Tech Atlanta GA 30332 USA Artera AI Berkeley CA USA Salesforce Res Washington DC USA
Despite the rapid progress in deep visual recognition, modern computer vision datasets significantly overrepresent the developed world and models trained on such datasets underperform on images from unseen geographies... 详细信息
来源: 评论
AAFormer: A Multi-Modal Transformer Network for Aerial Agricultural Images
AAFormer: A Multi-Modal Transformer Network for Aerial Agric...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Shen, Yao Wang, Lei Jin, Yue China Pacific Insurance Grp Co Ltd Shanghai Peoples R China East China Normal Univ Shanghai Peoples R China
The semantic segmentation of agricultural aerial images is very important for the recognition and analysis of farmland anomaly patterns, such as drydown, endrow, nutrient deficiency, etc. Methods for general semantic ... 详细信息
来源: 评论
Rethinking Supervised Depth Estimation for 360° Panoramic Imagery
Rethinking Supervised Depth Estimation for 360° Panoramic I...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: He, Lu Jian, Bing Wen, Yangming Zhu, Haichao Liu, Kelin Feng, Weiwei Liu, Shan Tencent Amer Palo Alto CA 94306 USA
Depth estimation from a single 360 degrees panorama image is a difficult task. It is an ill-posed problem to estimate depth maps from an RGB panorama image due to the intrinsic scale ambiguity issue. To mitigate the s... 详细信息
来源: 评论
Towards Explaining Image-Based Distribution Shifts
Towards Explaining Image-Based Distribution Shifts
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Kulinski, Sean Inouye, David I. Purdue Univ Sch Elect & Comp Engn W Lafayette IN 47907 USA
Distribution shift can have fundamental consequences such as signaling a change in the operating environment or significantly reducing the accuracy of downstream models. Thus, understanding such distribution shifts is... 详细信息
来源: 评论
Rank in Style: A Ranking-based Approach to Find Interpretable Directions
Rank in Style: A Ranking-based Approach to Find Interpretabl...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Kocasari, Umut Zaman, Kerem Tiftikci, Mert Simsar, Enis Yanardag, Pinar Bogazici Univ Istanbul Turkey TUM Munich Germany
Recent work such as StyleCLIP aims to harness the power of CLIP embeddings for controlled manipulations. Although these models are capable of manipulating images based on a text prompt, the success of the manipulation... 详细信息
来源: 评论
Conditioned and composed image retrieval combining and partially fine-tuning CLIP-based features
Conditioned and composed image retrieval combining and parti...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Baldrati, Alberto Bertini, Marco Uricchio, Tiberio Del Bimbo, Alberto Univ Firenze MICC Florence Italy Univ Pisa Pisa Italy
In this paper, we present an approach for conditioned and composed image retrieval based on CLIP features. In this extension of content-based image retrieval (CBIR) an image is combined with a text that provides infor... 详细信息
来源: 评论