ABSTRACT
We present a communication support system, namely We-toon, that can bridge the webtoon writers and artists during sketch revision (i.e., character design and draft revision). In the highly iterative design process between the webtoon writers and artists, writers often have difficulties in precisely articulating their feedback on sketches owing to their lack of drawing proficiency. This drawback makes the writers rely on textual descriptions and reference images found using search engines, leading to indirect and inefficient communications. Inspired by a formative study, we designed We-toon to help writers revise webtoon sketches and effectively communicate with artists. Through a GAN-based image synthesis and manipulation, We-toon can interactively generate diverse reference images and synthesize them locally on any user-provided image. Our user study with 24 professional webtoon authors demonstrated that We-toon outperforms the traditional methods in terms of communication effectiveness and the writers’ satisfaction level related to the revised image.
Supplemental Material
- Rinat Abdrashitov, Fanny Chevalier, and Karan Singh. 2020. Interactive Exploration and Refinement of Facial Expression Using Manifold Learning. In Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology. 778–790.Google ScholarDigital Library
- Yuval Alaluf, Omer Tov, Ron Mokady, Rinon Gal, and Amit Bermano. 2022. HyperStyle: StyleGAN Inversion With HyperNetworks for Real Image Editing. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 18511–18521.Google ScholarCross Ref
- Yazeed Alharbi and Peter Wonka. 2020. Disentangled Image Generation Through Structured Noise Injection. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).Google ScholarCross Ref
- Paul André, Jaime Teevan, and Susan T Dumais. 2009. From x-rays to silly putty via Uranus: serendipity and its role in web search. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. 2033–2036.Google ScholarDigital Library
- David Bau, Jun-Yan Zhu, Hendrik Strobelt, Bolei Zhou, Joshua B. Tenenbaum, William T. Freeman, and Antonio Torralba. 2019. GAN Dissection: Visualizing and Understanding Generative Adversarial Networks. In Proceedings of the International Conference on Learning Representations (ICLR).Google Scholar
- Gwern Branwen, Anonymous, and Danbooru Community. 2020. Danbooru2019: A Large-Scale Anime Character Illustration Dataset. https://www.gwern.net/Crops#figures. https://www.gwern.net/Crops#figures Accessed: August 29, 2021.Google Scholar
- Spencer Churchill. 2019. Anime face dataset. https://www.kaggle.com/splcher/animefacedataset Accessed: August 29, 2021.Google Scholar
- Edo Collins, Raja Bala, Bob Price, and Sabine Süsstrunk. 2020. Editing in Style: Uncovering the Local Semantics of GANs. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR).Google Scholar
- Sarah D’Angelo and Darren Gergle. 2018. An eye for design: gaze visualizations for remote collaborative work. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. 1–12.Google ScholarDigital Library
- Jeffrey T Hancock, Mor Naaman, and Karen Levy. 2020. AI-mediated communication: definition, research agenda, and ethical considerations. Journal of Computer-Mediated Communication 25, 1 (2020), 89–100.Google ScholarCross Ref
- Erik Härkönen, Aaron Hertzmann, Jaakko Lehtinen, and Sylvain Paris. 2020. GANSpace: Discovering Interpretable GAN Controls. In Advances in Neural Information Processing Systems, H. Larochelle, M. Ranzato, R. Hadsell, M. F. Balcan, and H. Lin (Eds.). Vol. 33. Curran Associates, Inc., 9841–9850. https://proceedings.neurips.cc/paper/2020/file/6fe43269967adbb64ec6149852b5cc3e-Paper.pdfGoogle Scholar
- Tero Karras, Miika Aittala, Janne Hellsten, Samuli Laine, Jaakko Lehtinen, and Timo Aila. 2020. Training Generative Adversarial Networks with Limited Data. In Proc. NeurIPS.Google Scholar
- Tero Karras, Samuli Laine, and Timo Aila. 2019. A Style-Based Generator Architecture for Generative Adversarial Networks. In 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 4396–4405. https://doi.org/10.1109/CVPR.2019.00453Google ScholarCross Ref
- Tero Karras, Samuli Laine, Miika Aittala, Janne Hellsten, Jaakko Lehtinen, and Timo Aila. 2020. Analyzing and Improving the Image Quality of StyleGAN. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).Google ScholarCross Ref
- Hyunsu Kim, Yunjey Choi, Junho Kim, Sungjoo Yoo, and Youngjung Uh. 2021. Exploiting Spatial Dimensions of Latent in GAN for Real-time Image Editing. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.Google ScholarCross Ref
- Tae Soo Kim, Seungsu Kim, Yoonseo Choi, and Juho Kim. 2021. Winder: Linking Speech and Visual Objects to Support Communication in Asynchronous Collaboration. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (Yokohama, Japan) (CHI ’21). Association for Computing Machinery, New York, NY, USA, Article 453, 17 pages. https://doi.org/10.1145/3411764.3445686Google ScholarDigital Library
- Robert Kraut, Carmen Egido, and Jolene Galegher. 1988. Patterns of contact and communication in scientific research collaboration. In Proceedings of the 1988 ACM conference on Computer-supported cooperative work. 1–12.Google ScholarDigital Library
- Yi-Chieh Lee, Naomi Yamashita, and Yun Huang. 2020. Designing a chatbot as a mediator for promoting deep self-disclosure to a real mental health professional. Proceedings of the ACM on Human-Computer Interaction 4, CSCW1(2020), 1–27.Google ScholarDigital Library
- Sheng Feng Li and Andy Hopper. 1998. A framework to integrate synchronous and asynchronous collaboration. In Proceedings Seventh IEEE International Workshop on Enabling Technologies: Infrastucture for Collaborative Enterprises (WET ICE’98)(Cat. No. 98TB100253). IEEE, 96–101.Google ScholarCross Ref
- Zhengqing Li, Theophilus Teo, Liwei Chan, Gun Lee, Matt Adcock, Mark Billinghurst, and Hideki Koike. 2020. OmniGlobeVR: A collaborative 360-degree communication system for VR. In Proceedings of the 2020 ACM Designing Interactive Systems Conference. 615–625.Google ScholarDigital Library
- Duri Long, Takeria Blunt, and Brian Magerko. 2021. Co-Designing AI Literacy Exhibits for Informal Learning Spaces. Proceedings of the ACM on Human-Computer Interaction 5, CSCW2(2021), 1–35.Google ScholarDigital Library
- Kai Lukoff, Taoxi Li, Yuan Zhuang, and Brian Y Lim. 2018. TableChat: mobile food journaling to facilitate family support for healthy eating. Proceedings of the ACM on Human-Computer Interaction 2, CSCW(2018), 1–28.Google ScholarDigital Library
- Pascal Molli, Hala Skaf-Molli, Gérald Oster, and Sébastien Jourdain. 2002. Sams: Synchronous, asynchronous, multi-synchronous environments. In The 7th international conference on computer supported cooperative work in design. IEEE, 80–84.Google ScholarCross Ref
- Xi Niu, Fakhri Abbas, Mary Lou Maher, and Kazjon Grace. 2018. Surprise me if you can: Serendipity in health information. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. 1–12.Google ScholarDigital Library
- Cecil Piya, Vinayak, Senthil Chandrasegaran, Niklas Elmqvist, and Karthik Ramani. 2017. Co-3Deator: A Team-First Collaborative 3D Design Ideation Tool. Association for Computing Machinery, New York, NY, USA, 6581–6592. https://doi.org/10.1145/3025453.3025825Google ScholarDigital Library
- Martin Ragot, Nicolas Martin, and Salomé Cojean. 2020. Ai-generated vs. human artworks. a perception bias towards artificial intelligence?. In Extended abstracts of the 2020 CHI conference on human factors in computing systems. 1–10.Google Scholar
- Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun. 2015. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks. In Advances in Neural Information Processing Systems, C. Cortes, N. Lawrence, D. Lee, M. Sugiyama, and R. Garnett (Eds.). Vol. 28. Curran Associates, Inc.https://proceedings.neurips.cc/paper/2015/file/14bfa6bb14875e45bba028a21ed38046-Paper.pdfGoogle Scholar
- Daniel Roich, Ron Mokady, Amit H Bermano, and Daniel Cohen-Or. 2021. Pivotal Tuning for Latent-based Editing of Real Images. arXiv preprint arXiv:2106.05744(2021).Google Scholar
- Ugo Braga Sangiorgi, François Beuvens, and Jean Vanderdonckt. 2012. User interface design by collaborative sketching. In Proceedings of the Designing Interactive Systems Conference. 378–387.Google ScholarDigital Library
- Axel Sauer, Katja Schwarz, and Andreas Geiger. 2022. StyleGAN-XL: Scaling StyleGAN to Large Diverse Datasets. arXiv preprint arXiv:2202.00273(2022).Google Scholar
- Isabella Seeber, Eva Bittner, Robert O Briggs, Triparna De Vreede, Gert-Jan De Vreede, Aaron Elkins, Ronald Maier, Alexander B Merz, Sarah Oeste-Reiß, Nils Randrup, 2020. Machines as teammates: A research agenda on AI in team collaboration. Information & management 57, 2 (2020), 103174.Google Scholar
- Yujun Shen and Bolei Zhou. 2021. Closed-Form Factorization of Latent Semantics in GANs. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 1532–1540.Google ScholarCross Ref
- Minhyang (Mia) Suh, Emily Youngblom, Michael Terry, and Carrie J Cai. 2021. AI as Social Glue: Uncovering the Roles of Deep Generative AI during Social Music Composition. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (Yokohama, Japan) (CHI ’21). Association for Computing Machinery, New York, NY, USA, Article 582, 11 pages. https://doi.org/10.1145/3411764.3445219Google ScholarDigital Library
- Ryohei Suzuki, Masanori Koyama, Takeru Miyato, and Taizan Yonetsuji. 2018. Collaging on Internal Representations: An Intuitive Approach for Semantic Transfiguration. CoRR abs/1811.10153(2018). arxiv:1811.10153http://arxiv.org/abs/1811.10153Google Scholar
- Jaime Teevan, Shamsi T. Iqbal, and Curtis von Veh. 2016. Supporting Collaborative Writing with Microtasks. Association for Computing Machinery, New York, NY, USA, 2657–2668. https://doi.org/10.1145/2858036.2858108Google ScholarDigital Library
- Balasaravanan Thoravi Kumaravel, Cuong Nguyen, Stephen DiVerdi, and Bjoern Hartmann. 2020. TransceiVR: Bridging Asymmetrical Communication Between VR Users and External Collaborators. In Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology. 182–195.Google ScholarDigital Library
- Alice Thudt, Uta Hinrichs, and Sheelagh Carpendale. 2012. The bohemian bookshelf: supporting serendipitous book discoveries through information visualization. In Proceedings of the SIGCHI Conference on human factors in computing systems. 1461–1470.Google ScholarDigital Library
- Sunny Tian, Amy X Zhang, and David Karger. 2021. A System for Interleaving Discussion and Summarization in Online Collaboration. Proceedings of the ACM on Human-Computer Interaction 4, CSCW3(2021), 1–27.Google ScholarDigital Library
- Carlos Toxtli, Andrés Monroy-Hernández, and Justin Cranshaw. 2018. Understanding chatbot-mediated task management. In Proceedings of the 2018 CHI conference on human factors in computing systems. 1–6.Google ScholarDigital Library
- Dakuo Wang, Elizabeth Churchill, Pattie Maes, Xiangmin Fan, Ben Shneiderman, Yuanchun Shi, and Qianying Wang. 2020. From human-human collaboration to human-ai collaboration: Designing ai systems that can work together with people. In Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems. 1–6.Google ScholarDigital Library
- Christine Wolf and Jeanette Blomberg. 2019. Evaluating the promise of human-algorithm collaborations in everyday work practices. Proceedings of the ACM on Human-Computer Interaction 3, CSCW(2019), 1–23.Google ScholarDigital Library
- Te-Yen Wu, Jun Gong, Teddy Seyed, and Xing-Dong Yang. 2019. Proxino: enabling prototyping of virtual circuits with physical proxies. In Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology. 121–132.Google ScholarDigital Library
- Zhenpeng Zhao, Sriram Karthik Badam, Senthil Chandrasegaran, Deok Gun Park, Niklas LE Elmqvist, Lorraine Kisselburgh, and Karthik Ramani. 2014. skWiki: a multimedia sketching system for collaborative creativity. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. 1235–1244.Google ScholarDigital Library
Index Terms
- We-toon: A Communication Support System between Writers and Artists in Collaborative Webtoon Sketch Revision
Recommendations
Sketch or Play?: LEGO® Stimulates Divergent Thinking for Non-sketchers in HCI Conceptual Ideation
CHI EA '19: Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing SystemsSketching is known to support divergent thinking during conceptual ideation. Yet, in HCI teams, non-designers are known to be reluctant to sketch. Looking for a tool that could support non-designers' divergent thinking to creatively offset familiar ...
A Handwritten Japanese Historical Kana Reprint Support System: Development of a Graphical User Interface
DocEng '18: Proceedings of the ACM Symposium on Document Engineering 2018Reprint of Japanese historical manuscripts is time-consuming and requires training because they are hand-written, and may contain characters different from those currently used. We proposed a framework for assisting the human process for reading ...
VujaDessin: A Sketch Learning Support System Using a Blurred Motif Object
Human-Computer Interaction. Design Practice in Contemporary SocietiesAbstractSketch is a creative activity that anybody can start casually and often used as training to begin a full-fledged painting. Since beginners sometimes feel difficulty to draw accurate sketch, various tutoring systems of sketch have been developed. ...
Comments