M2FN: Multi-step modality fusion for advertisement image assessment (original) (raw)
Related papers
ArXiv, 2019
Exploring Online Ad Images Using a Deep Convolutional Neural Network Approach
The 3rd IEEE International Conference on Smart Data (SmartData), 2017
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining - KDD '19, 2019
Enhancing Dynamic Image Advertising with Vision-Language Pre-training
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval
IJERT-Image Aesthetics Assessment using Deep Learning (based on High Level Image Attributes)
International Journal of Engineering Research and Technology (IJERT), 2020
Image Aesthetics Assessment using Deep Learning (based on High Level Image Attributes)
International journal of engineering research and technology, 2020
Deep Learning Based Modeling in Computational Advertising: A Winning Formula
Industrial Engineering & Management, 2018
AdsCVLR: Commercial Visual-Linguistic Representation Modeling in Sponsored Search
Proceedings of the 30th ACM International Conference on Multimedia
Photo Aesthetics Ranking Network with Attributes and Content Adaptation
Computer Vision – ECCV 2016, 2016
Tsinghua Science and Technology, 2022
Understanding Visual Ads by Aligning Symbols and Objects using Co-Attention
2018
Predicting Sentiments in Image Advertisements using Semantic Relations among Sentiment Labels
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2020
Multimodal Content Analysis for Effective Advertisements on YouTube
2017 IEEE International Conference on Data Mining (ICDM), 2017
SoCraft: Advertiser-level Predictive Scoring for Creative Performance on Meta
Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining
ADNet: A Deep Network for Detecting Adverts
2018
Deep Learning Model with Transfer Learning to Infer Personal Preferences in Images
Applied Sciences, 2020
Brain-Inspired Deep Networks for Image Aesthetics Assessment
ArXiv, 2016
Effective Aesthetics Prediction with Multi-level Spatially Pooled Features
CVPR, 2019
Learning Photography Aesthetics with Deep CNNs
arXiv (Cornell University), 2017
Comparing Neural and Attractiveness-based Visual Features for Artwork Recommendation
Proceedings of the 2nd Workshop on Deep Learning for Recommender Systems, 2017
Measuring photography aesthetics with deep CNNs
IET Image Processing, 2020
AD or Non-AD: A Deep Learning Approach to Detect Advertisements from Magazines
Entropy, 2018
Multimodal Ad Recall Prediction Based on Viewer’s and Ad Features
2020
ArXiv, 2016
Image Aesthetics Assessment Using Multi Channel Convolutional Neural Networks
Computer Vision and Image Processing, 2020
Automatic Understanding of Image and Video Advertisements
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Deep learning in digital marketing: brand detection and emotion recognition
International Journal of Machine Intelligence and Sensory Signal Processing, 2017
The Focus–Aspect–Value model for predicting subjective visual attributes
International Journal of Multimedia Information Retrieval, 2020
Image Aesthetic Assessment: A Comparative Study of Hand-Crafted & Deep Learning Models
IEEE Access
Persuasion Strategies in Advertisements: Dataset, Modeling, and Baselines
SalAds: A Multimodal Approach for Contextual Video Advertising
arXiv (Cornell University), 2016
Automatic measurement of ad preferences from facial responses gathered over the Internet
Image and Vision Computing, 2014
Multim. Tools Appl., 2021
Contextual in-image advertising
2008