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To overcome the above problem, Spatio-Temporal Inference Transformer Network (STITN) has been proposed. The STITN aligns the frames to be inpainted and concurrently inpaints all the frames, and a spatio-temporal adversarial loss function improves the STITN.\u00a0Our method performs considerably better than the existing deep learning approaches in quantitative and qualitative evaluation. <\/jats:p>","DOI":"10.1142\/s0219467823500079","type":"journal-article","created":{"date-parts":[[2021,12,18]],"date-time":"2021-12-18T09:47:22Z","timestamp":1639820842000},"source":"Crossref","is-referenced-by-count":2,"title":["Spatio-Temporal Inference Transformer Network for Video Inpainting"],"prefix":"10.1142","volume":"23","author":[{"given":"Gajanan","family":"Tudavekar","sequence":"first","affiliation":[{"name":"Department of Electronics & Communication Engineering, Angadi Institute of Technology and Management, Belagavi 590009, Karnataka, India"},{"name":"Department of Electronics & Communication Engineering, KLS Gogte Institute of Technology \u201cJnana Ganga\u201d, Belagavi 590008, Karnataka, India"}]},{"given":"Santosh S.","family":"Saraf","sequence":"additional","affiliation":[{"name":"Department of Electronics & Communication Engineering, KLS Gogte Institute of Technology \u201cJnana Ganga\u201d, Belagavi 590008, Karnataka, India"}]},{"given":"Sanjay R.","family":"Patil","sequence":"additional","affiliation":[{"name":"Department of Electronics & Telecommunication Engineering, Dnyanshree Institute of Engineering and Technology, Sajjangad Road, Satara 415013, Maharashtra, India"}]}],"member":"219","published-online":{"date-parts":[[2021,12,18]]},"reference":[{"issue":"4","key":"S0219467823500079BIB001","doi-asserted-by":"crossref","first-page":"314","DOI":"10.1049\/trit.2019.0045","volume":"5","author":"Tudavekar G.","year":"2020","journal-title":"CAAI Trans. 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