{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,22]],"date-time":"2025-04-22T04:06:53Z","timestamp":1745294813416,"version":"3.40.4"},"publisher-location":"Cham","reference-count":32,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031901669","type":"print"},{"value":"9783031901676","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-90167-6_5","type":"book-chapter","created":{"date-parts":[[2025,4,22]],"date-time":"2025-04-22T02:14:40Z","timestamp":1745288080000},"page":"66-81","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["The Importance of\u00a0Context in\u00a0Image Generation: A Case Study for\u00a0Video Game Sprites"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7578-6173","authenticated-orcid":false,"given":"Roberto","family":"Gallotta","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5554-1961","authenticated-orcid":false,"given":"Antonios","family":"Liapis","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7793-1450","authenticated-orcid":false,"given":"Georgios N.","family":"Yannakakis","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,4,20]]},"reference":[{"key":"5_CR1","doi-asserted-by":"crossref","unstructured":"Ait\u00a0Baha, T., El\u00a0Hajji, M., Es-Saady, Y., Fadili, H.: The power of personalization: a systematic review of personality-adaptive chatbots. SN Comput. Sci. 4(661) (2023)","DOI":"10.1007\/s42979-023-02092-6"},{"key":"5_CR2","unstructured":"Brown, T.B., et al.: Language models are few-shot learners. arXiv preprint arXiv:2005.14165 (2020)"},{"key":"5_CR3","doi-asserted-by":"crossref","unstructured":"B\u00f6ffel, C., W\u00fcrger, S., M\u00fcsseler, J., Schlittmeier, S.J.: Character customization with cosmetic microtransactions in games: subjective experience and objective performance. Front. Psychol. 12 (2022)","DOI":"10.3389\/fpsyg.2021.770139"},{"key":"5_CR4","doi-asserted-by":"crossref","unstructured":"Crowson, K., et al.: VQGAN-CLIP: open domain image generation and editing with natural language guidance. In: Proceedings of the European Conference on Computer Vision, pp. 88\u2013105. Springer, Cham (2022)","DOI":"10.1007\/978-3-031-19836-6_6"},{"key":"5_CR5","unstructured":"damian0815: Compel (2023). https:\/\/github.com\/damian0815\/compel"},{"key":"5_CR6","unstructured":"danielgatis: Rembg (2023). https:\/\/github.com\/danielgatis\/rembg"},{"key":"5_CR7","first-page":"8780","volume":"34","author":"P Dhariwal","year":"2021","unstructured":"Dhariwal, P., Nichol, A.: Diffusion models beat GANs on image synthesis. Adv. Neural. Inf. Process. Syst. 34, 8780\u20138794 (2021)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"5_CR8","doi-asserted-by":"crossref","unstructured":"Gallotta, R., Liapis, A., Yannakakis, G.N.: Consistent game content creation via function calling for large language models. In: Proceedings of the IEEE Conference on Games (2024)","DOI":"10.1109\/CoG60054.2024.10645599"},{"key":"5_CR9","first-page":"6840","volume":"33","author":"J Ho","year":"2020","unstructured":"Ho, J., Jain, A., Abbeel, P.: Denoising diffusion probabilistic models. Adv. Neural. Inf. Process. Syst. 33, 6840\u20136851 (2020)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"5_CR10","unstructured":"Hu, E.J., et al.: Lora: low-rank adaptation of large language models. arXiv preprint arXiv:2106.09685 (2021)"},{"issue":"11","key":"5_CR11","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1167\/6.11.13","volume":"6","author":"F J\u00e4kel","year":"2006","unstructured":"J\u00e4kel, F., Wichmann, F.A.: Spatial four-alternative forced-choice method is the preferred psychophysical method for na\u00efve observers. J. Vis. 6(11), 13 (2006)","journal-title":"J. Vis."},{"key":"5_CR12","doi-asserted-by":"crossref","unstructured":"Kane, S.K., Linam-Church, B., Althoff, K., McCall, D.: What we talk about: designing a context-aware communication tool for people with aphasia. In: Proceedings of the International SIGACCESS Conference on Computers and Accessibility, pp. 49\u201356. Association for Computing Machinery (2012)","DOI":"10.1145\/2384916.2384926"},{"key":"5_CR13","doi-asserted-by":"crossref","unstructured":"Kastryulin, S., Zakirov, J., Prokopenko, D., Dylov, D.V.: PyTorch image quality: metrics for image quality assessment. arXiv preprint arXiv:2208.14818 (2022)","DOI":"10.2139\/ssrn.4206741"},{"issue":"1\u20132","key":"5_CR14","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1093\/biomet\/30.1-2.81","volume":"30","author":"MG Kendall","year":"1938","unstructured":"Kendall, M.G.: A new measure of rank correlation. Biometrika 30(1\u20132), 81\u201393 (1938)","journal-title":"Biometrika"},{"key":"5_CR15","unstructured":"Li, J., Li, D., Xiong, C., Hoi, S.: BLIP: bootstrapping language-image pre-training for unified vision-language understanding and generation. In: Proceedings of the International Conference on Machine Learning (2022)"},{"key":"5_CR16","doi-asserted-by":"crossref","unstructured":"Liapis, A., Smith, G., Shaker, N.: Mixed-initiative content creation. In: Shaker, N., Togelius, J., Nelson, M.J. (eds.) Procedural Content Generation in Games: A Textbook and an Overview of Current Research, pp. 195\u2013214. Springer, Cham (2016)","DOI":"10.1007\/978-3-319-42716-4_11"},{"key":"5_CR17","unstructured":"Liapis, A., Yannakakis, G.N., Togelius, J.: Computational game creativity. In: Proceedings of the International Conference on Computational Creativity (2014)"},{"key":"5_CR18","first-page":"43","volume":"160","author":"P Machado","year":"2015","unstructured":"Machado, P., Romero, J., Nadal, M., Santos, A., Correia, J., Carballal, A.: Computerized measures of visual complexity. Acta Physiol. (Oxf) 160, 43\u201357 (2015)","journal-title":"Acta Physiol. (Oxf)"},{"key":"5_CR19","doi-asserted-by":"crossref","unstructured":"Mittal, A., Moorthy, A.K., Bovik, A.C.: Blind\/referenceless image spatial quality evaluator. In: Proceedings of the Asilomar Conference on Signals, Systems and Computers (2011)","DOI":"10.1109\/ACSSC.2011.6190099"},{"key":"5_CR20","doi-asserted-by":"crossref","unstructured":"Plitsis, M., Kouzelis, T., Paraskevopoulos, G., Katsouros, V., Panagakis, Y.: Investigating personalization methods in text to music generation. arXiv preprint arXiv:2309.11140 (2023)","DOI":"10.1109\/ICASSP48485.2024.10446869"},{"key":"5_CR21","unstructured":"Radford, A., et al.: Learning transferable visual models from natural language supervision. In: Proceedings of the International Conference on Machine Learning. Proceedings of Machine Learning Research, vol.\u00a0139, pp. 8748\u20138763. PMLR (2021)"},{"key":"5_CR22","unstructured":"Ramesh, A., et al.: Zero-shot text-to-image generation. In: Proceedings of the International Conference on Machine Learning. Proceedings of Machine Learning Research, vol.\u00a0139, pp. 8821\u20138831. PMLR (2021)"},{"key":"5_CR23","doi-asserted-by":"crossref","unstructured":"Rombach, R., Blattmann, A., Lorenz, D., Esser, P., Ommer, B.: High-resolution image synthesis with latent diffusion models. arXiv preprint arXiv:2112.10752 (2022)","DOI":"10.1109\/CVPR52688.2022.01042"},{"key":"5_CR24","doi-asserted-by":"crossref","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-Net: convolutional networks for biomedical image segmentation. In: Proceedings of the International Conference on Medical Image Computing and Computer-Assisted Intervention (2015)","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"5_CR25","doi-asserted-by":"crossref","unstructured":"Schaub, F., K\u00f6nings, B., Lang, P., Wiedersheim, B., Winkler, C., Weber, M.: PriCal: context-adaptive privacy in ambient calendar displays. In: Proceedings of the ACM International Joint Conference on Pervasive and Ubiquitous Computing, pp. 499\u2013510. Association for Computing Machinery (2014)","DOI":"10.1145\/2632048.2632087"},{"key":"5_CR26","unstructured":"Sohl-Dickstein, J., Weiss, E., Maheswaranathan, N., Ganguli, S.: Deep unsupervised learning using nonequilibrium thermodynamics. In: Proceedings of the International Conference on Machine Learning (2015)"},{"key":"5_CR27","doi-asserted-by":"crossref","unstructured":"Xie, S., Tu, Z.: Holistically-nested edge detection. In: Proceedings of IEEE International Conference on Computer Vision (2015)","DOI":"10.1109\/ICCV.2015.164"},{"key":"5_CR28","doi-asserted-by":"crossref","unstructured":"Zammit, M., Liapis, A., Yannakakis, G.N.: CrawLLM: theming games with large language models. In: Proceedings of the IEEE Conference on Games (2024)","DOI":"10.1109\/CoG60054.2024.10645576"},{"key":"5_CR29","doi-asserted-by":"crossref","unstructured":"Zammit, M., Liapis, A., Yannakakis, G.N.: MAP-Elites with transverse assessment for multimodal problems in creative domains. In: Proceedings of the International Conference on Computational Intelligence in Music, Sound, Art and Design (EvoMusArt) (2024)","DOI":"10.1007\/978-3-031-56992-0_26"},{"key":"5_CR30","doi-asserted-by":"crossref","unstructured":"Zhang, L., Rao, A., Agrawala, M.: Adding conditional control to text-to-image diffusion models. In: Proceedings of the IEEE International Conference on Computer Vision (2023)","DOI":"10.1109\/ICCV51070.2023.00355"},{"key":"5_CR31","doi-asserted-by":"crossref","unstructured":"Zhang, R., Isola, P., Efros, A.A., Shechtman, E., Wang, O.: The unreasonable effectiveness of deep features as a perceptual metric. In: Proceedings of the Conference on Computer Vision and Pattern Recognition (2018)","DOI":"10.1109\/CVPR.2018.00068"},{"key":"5_CR32","doi-asserted-by":"crossref","unstructured":"Zhu, J., Onta\u00f1\u00f3n, S.: Player-centered AI for automatic game personalization: open problems. arXiv preprint arXiv:2102.07548 (2021)","DOI":"10.1145\/3402942.3402951"}],"container-title":["Lecture Notes in Computer Science","Artificial Intelligence in Music, Sound, Art and Design"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-90167-6_5","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,22]],"date-time":"2025-04-22T02:15:01Z","timestamp":1745288101000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-90167-6_5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031901669","9783031901676"],"references-count":32,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-90167-6_5","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"20 April 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"EvoMUSART","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computational Intelligence in Music, Sound, Art and Design (Part of EvoStar)","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Trieste","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 April 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 April 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"evomusart2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.evostar.org\/2025\/evomusart\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}