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Preference-Based Image Generation
2020
2020 IEEE Winter Conference on Applications of Computer Vision (WACV)
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In this paper, we introduce the Preference-Based Image Generation (PbIG), a new method to retrieve the corresponding latent code of the user's mental image. ...
We propose to adopt preference-based reinforcement learning, which learns from a user's judgment of the generated images by a pretrained generative model. ...
Preference-Based Image Generation (PbIG) In our proposed Preference-Based Image Generation (PbIG) the state of environment does not change as the user has a fixed mental image at all time, and taking new ...
doi:10.1109/wacv45572.2020.9093406
dblp:conf/wacv/KazemiTN20
fatcat:a7lvwpxf3nfwdiqrbgo37xgh2a
Preference-based Evaluation Metrics for Web Image Search
2020
Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval
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Compared to general web search, web image search may be an even better fit for preference-based evaluation because of its grid-based presentation style. ...
While preference judgments have been studied extensively for general web search, there exists no thorough investigation on how preference judgments and preference-based evaluation metrics can be used to ...
In web image search, grid-based result panels are used instead of the linear result lists that are common in general web search. ...
doi:10.1145/3397271.3401146
dblp:conf/sigir/XieMLRCZM20
fatcat:wgimluovu5frlcrsmivd7mznfq
Joint regression and learning from pairwise rankings for personalized image aesthetic assessment
2021
Computational Visual Media
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a generic aesthetic assessment model by CNN-based regression. ...
However, these methods focus primarily on predicting generally perceived preference of an image, making them usually have limited practicability, since each user may have completely different preferences ...
Generic image aesthetic regression With the collected personal images, we regress a generic aesthetic model that numerically describes the universal visual preference for images of similar categories. ...
doi:10.1007/s41095-021-0207-y
fatcat:yve552ozqbahzh66bhkl6tn3lu
Deep Learning Model with Transfer Learning to Infer Personal Preferences in Images
2020
Applied Sciences
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In this paper, we propose a deep convolutional neural network model with transfer learning that reflects personal preferences from inter-domain databases of images having atypical visual characteristics ...
The proposed model utilized three public image databases (Fashion-MNIST, Labeled Faces in the Wild [LFW], and Indoor Scene Recognition) that include images with atypical visual characteristics in order ...
Structure of Grad-CAM for generating a heat map reflecting the user's preference based on atypical features.
Figure 4 . 4 Figure 4. Fashion-MNIST dataset images and labels [6,16]. ...
doi:10.3390/app10217641
fatcat:6cynirgvrzhffg7geh7tkmftby
USER'S PREFERENCE-BASED COLOR TRANSFORMATION USING INTERACTIVE GENETIC ALGORITHM
[article]
2010
Eurographics State of the Art Reports
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To obtain general preferences for color, we first divided the images into two categories as favourable and unfavourable groups based on the users' evaluation. ...
In this paper, we propose a new color transform method in the image based on the user's preferences. ...
If we can transform colors in the captured images into favorable and unfavorable colors, a user can easily create his own preferred images. ...
doi:10.2312/egp.20101027
fatcat:iz66vmyxnbdtpicfl67ohfpgxm
Preferred Racial Skin Color Reproduction in an Image based on Race Classification
2015
Journal of Imaging Science and Technology
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Based on this classification, the racial preferred skin color for each detected skin region is then selected from candidate racial preferred skin colors that are predefined in a database generated through ...
Kim, Kyung, and Ha: Preferred racial skin color reproduction in an image based on race classification Figure 1. Block diagram of the proposed skin color reproduction. ...
For Asians, 360 prototype skin images are generated by changing the hue and saturation values under a predefined skin color based on HSV color space. ...
doi:10.2352/j.imagingsci.technol.2015.59.2.020504
fatcat:24bzpm3gxzcn7bp2j5mh3jn5wi
Which is the Better Inpainted Image?Training Data Generation Without Any Manual Operations
2018
International Journal of Computer Vision
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Thus, existing learning-based image quality assessment (IQA) methods for inpainting require subjectively annotated data for training. ...
We also propose a masking method for generating training data towards fully automated training data generation. ...
Shohei Mori for sharing the image inpainting implementation. ...
doi:10.1007/s11263-018-1132-0
fatcat:ofza7jlki5cz5ollmawiel4yca
Assessment of Color Perception and Preference with Eye-Tracking Analysis in a Dental Treatment Environment
2021
International Journal of Environmental Research and Public Health
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In addition, for the psychological color images associated with color preference, the subjects tended to prefer images such as warmth, friendliness, and calmness. ...
This study aimed to investigate gaze characteristics based on a color preference survey of the dental unit chair, which has the most influence on spatial perception in the dental treatment environment, ...
It is difficult to generalize the result of color preference based on the gaze analysis as a method for establishing a color scheme for a medical environment. ...
doi:10.3390/ijerph18157981
fatcat:fttmozxwz5crpczv6nr344budm
Visually-Aware Fashion Recommendation and Design with Generative Image Models
[article]
2017
arXiv
pre-print
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Furthermore, we show that our model can be used generatively, i.e., given a user and a product category, we can generate new images (i.e., clothing items) that are most consistent with their personal taste ...
Here, we seek to extend this contribution by showing that recommendation performance can be significantly improved by learning 'fashion aware' image representations directly, i.e., by training the image ...
(based on Generative Adversarial Networks). ...
arXiv:1711.02231v1
fatcat:xytgylq6bvbthhcebq3hccunfe
Development of Fashion Product Retrieval and Recommendations Model Based on Deep Learning
2020
Electronics
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The vector-based preference fashion recommendation model also showed positive performance. ...
It was found that the "Precision at 5" of the image-based similar product retrieval model was 0.774 and that of the sketch-based similar product retrieval model was 0.445. ...
As the proposed images were filtered by professionals, general users can select their preferred style from the images that were already screened for uncomfortable or unattractive styles. ...
doi:10.3390/electronics9030508
fatcat:kmffxze2zbemfhqwxcioksveui
Learning Long- and Short-Term User Literal-Preference with Multimodal Hierarchical Transformer Network for Personalized Image Caption
2020
PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE
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Personalized image caption, a natural extension of the standard image caption task, requires to generate brief image descriptions tailored for users' writing style and traits, and is more practical to ...
It learns short-term user literal-preference based on users' recent captions through a short-term user encoder at the low level. ...
The retrieval based models in the first part of the table perform poorly compared with other generative models. ...
doi:10.1609/aaai.v34i05.6503
fatcat:fmqhiw2o3zdtppmgekcczebvbe
Human-in-the-Loop Design with Machine Learning
2019
Proceedings of the International Conference on Engineering Design
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The results indicate that the method can generate preferred designs styles guided by the preference related brain signals. ...
Secondly, a GAN model is trained conditioned on the encoded EEG features to generate design images. ...
Designers could have a prejudgment based on these generated images. ...
doi:10.1017/dsi.2019.264
fatcat:egboi5gc7ja5ba34ra7ukezuim
Evolutionary programming based recommendation system for online shopping
2013
2013 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference
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In this paper, we propose an interactive evolutionary programming based recommendation system for online shopping that estimates the human preference based on eye movement analysis. ...
Therefore, in the proposed system, human preference is measured from the way the human subjects look at the images of different clothes. ...
In other words, when several images are presented simultaneously there exists a correlation between accumulated fixation time and the viewer's preference for one image over others [8] . ...
doi:10.1109/apsipa.2013.6694236
dblp:conf/apsipa/JungMMFIL13
fatcat:zlaeu6nhgzbhza3kyf6djfebxi
Knowing a tree from the forest
2003
Proceedings of the eleventh ACM international conference on Multimedia - MULTIMEDIA '03
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In the second setting, we report evaluations based on user preferences collected through an online web-based survey. ...
AIR is of great interests to us because of its application potentials and interesting research challengesthe retrieval is not only based on painting contents or styles, but also heavily based on user preference ...
Based on the profile type, we generate a number of examples, with approximately 1/3 liked images and 2/3 disliked ones, to feed the art image retrieval system. ...
doi:10.1145/957142.957145
fatcat:5qhojr5yrrehzf2y6pecpknqyu
Knowing a tree from the forest
2003
Proceedings of the eleventh ACM international conference on Multimedia - MULTIMEDIA '03
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In the second setting, we report evaluations based on user preferences collected through an online web-based survey. ...
AIR is of great interests to us because of its application potentials and interesting research challengesthe retrieval is not only based on painting contents or styles, but also heavily based on user preference ...
Based on the profile type, we generate a number of examples, with approximately 1/3 liked images and 2/3 disliked ones, to feed the art image retrieval system. ...
doi:10.1145/957013.957145
dblp:conf/mm/YuMTXHZK03
fatcat:wwtdpdmuh5csdiuiuatzkw6eny
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