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Graph."],"published-print":{"date-parts":[[2025,8,1]]},"abstract":"<jats:p>\n                    We introduce\n                    <jats:bold>ViSA<\/jats:bold>\n                    (Virtual Stunt Actors), an interactive animation system designed to create realistic ballistic stunt actions frequently seen in filmmaking and TV production. By providing spatial constraints suitable for the desired stunt scene, our system generates physically plausible motions satisfying the given constraints. The problem is formulated as a deep reinforcement learning task, incorporating a novel state and action spaces, as well as straightforward yet effective rewards for ballistic stunt actions. Users can receive a fast response within several minutes and continue to choreograph complex stunt scenes in an interactive manner. We demonstrate ballistic stunt scenes resembling those in various films and TV dramas, such as traffic accidents, falling down stairs, and falls from buildings. The effectiveness of the technical components and design choices in our system is demonstrated through extensive comparisons, analyses, and ablation studies.\n                  <\/jats:p>","DOI":"10.1145\/3731424","type":"journal-article","created":{"date-parts":[[2025,7,27]],"date-time":"2025-07-27T04:02:22Z","timestamp":1753588942000},"page":"1-15","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["ViSA: Physics-based Virtual Stunt Actors for Ballistic Stunts"],"prefix":"10.1145","volume":"44","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0712-2663","authenticated-orcid":false,"given":"Minseok","family":"Kim","sequence":"first","affiliation":[{"name":"Computer Science and Engineering \/ Seoul National University \/ Intelligent Motion Lab, Seoul National University, Seoul, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1823-4596","authenticated-orcid":false,"given":"Wonjeong","family":"Seo","sequence":"additional","affiliation":[{"name":"Computer Science and Engineering \/ Seoul National University \/ Intelligent Motion Lab, Seoul National University, Seoul, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6604-4709","authenticated-orcid":false,"given":"Sung-Hee","family":"Lee","sequence":"additional","affiliation":[{"name":"Graduate School of Culture Technology \/ KAIST \/ Lifelike Avatar &amp; Agent Lab, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5510-6425","authenticated-orcid":false,"given":"Jungdam","family":"Won","sequence":"additional","affiliation":[{"name":"Computer Science and Engineering \/ Seoul National University \/ Intelligent Motion Lab, Seoul National University, Seoul, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2025,7,27]]},"reference":[{"key":"e_1_2_2_1_1","volume-title":"Martin De Lasa, and Aaron Hertzmann","author":"Borno Mazen Al","year":"2012","unstructured":"Mazen Al Borno, Martin De Lasa, and Aaron Hertzmann. 2012. 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