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BAM! The Behance Artistic Media Dataset for Recognition Beyond Photography [article]

Michael J. Wilber, Chen Fang, Hailin Jin, Aaron Hertzmann, John Collomosse, Serge Belongie
2017 arXiv   pre-print
We believe our Behance Artistic Media dataset will be a good starting point for researchers wishing to study artistic imagery and relevant problems.  ...  We annotate Behance imagery with rich attribute labels for content, emotions, and artistic media.  ...  BAM! The Behance Artistic Media Dataset for Recognition Beyond Photography Michael J.  ... 
arXiv:1704.08614v2 fatcat:vgjcnt7tyrhcvdsfctwvyyvvzu

Gaudí: Conversational Interactions with Deep Representations to Generate Image Collections [article]

Victor S. Bursztyn, Jennifer Healey, Vishwa Vinay
2021 arXiv   pre-print
Based on recent advances in realistic language modeling (GPT-3) and cross-modal representations (CLIP), Gaud\'i was developed to help designers search for inspirational images using natural language.  ...  Gaud\'i transforms this process into a conversation where the user is gradually detailing the mood-board's theme.  ...  Bam! the behance artistic media dataset for recognition beyond photography.  ... 
arXiv:2112.04404v1 fatcat:vttgytmprnda7pprvukffktt6i

Photozilla: A Large-Scale Photography Dataset and Visual Embedding for 20 Photography Styles [article]

Trisha Singhal, Junhua Liu, Lucienne T. M. Blessing, Kwan Hui Lim
2021 arXiv   pre-print
The advent of social media platforms has been a catalyst for the development of digital photography that engendered a boom in vision applications.  ...  We report an accuracy of over 68% for identifying 10 other distinct types of photography styles. This dataset can be found at  ...  [25] focused on contemporary artwork and featured an artistic imagery dataset, BAM, collected from the Behance website.  ... 
arXiv:2106.11359v1 fatcat:ivzvaayo4zgovgyb7xr6x23cie

Deep learning approaches to pattern extraction and recognition in paintings and drawings: an overview

Giovanna Castellano, Gennaro Vessio
2021 Neural computing & applications (Print)  
AbstractThis paper provides an overview of some of the most relevant deep learning approaches to pattern extraction and recognition in visual arts, particularly painting and drawing.  ...  Recent advances in deep learning and computer vision, coupled with the growing availability of large digitized visual art collections, have opened new opportunities for computer science researchers to  ...  Acknowledgements Gennaro Vessio acknowledges the financial support of the Italian Ministry of University and Research through the PON AIM 1852414 project.  ... 
doi:10.1007/s00521-021-05893-z fatcat:elqzw3hzbzgodotie6ndih537u

The ArtBench Dataset: Benchmarking Generative Models with Artworks [article]

Peiyuan Liao, Xiuyu Li, Xihui Liu, Kurt Keutzer
2022 arXiv   pre-print
We introduce ArtBench-10, the first class-balanced, high-quality, cleanly annotated, and standardized dataset for benchmarking artwork generation.  ...  The dataset is available at under a Fair Use license.  ...  The authors would also like to express gratitude towards WikiArt, the Surrealism Website, Japanese Woodblock Print Search, and all the artists who appeared in the dataset.  ... 
arXiv:2206.11404v1 fatcat:6ci5o75ttnglff4gab5bczi6la

Learning perceptual similarity from crowds and machines

Michael Wilber
Finally, we will discuss our work on creating a large-scale dataset of artwork that the research community can use to explore these ideas. out my mentor, Serge Belongie, whose patient guidance was instrumental  ...  I have also had the pleasure of relying on the support and encouragement of many peers. This thesis is based off of joint work with Andreas  ...  THE BEHANCE ARTISTIC MEDIA DATASET FOR RECOGNITION BEYOND PHOTOGRAPHY "Art is an effort to create, beside the real world, a more humane world." - André Maurois Recent advances in Computer Vision have  ... 
doi:10.7298/x4fx77qk fatcat:u4igmz453fdpdi23nyuyp4ez2a