{"title":"基于深度学习的动画场景自动深度估计和背景模糊","authors":"Chao He, Yi Jia","doi":"10.18280/ts.400539","DOIUrl":null,"url":null,"abstract":"Animation technology enables more accurate depth estimation and background blurring of animated scenes as it can enhance the sense of reality of the vision and increase its depth, thus it has become a hot spot in relevant research and production these days. However, although deep learning has made significant progresses in many research fields, its application in depth estimation and background blurring of animated scenes is still facing a few challenges. Most available technologies are for real world images, not animations, so there are certain difficulties capturing the unique styles of animations and their details. This study proposes two technical schemes specifically designed for animated scenes: a depth estimation model based on DenseNet , and a deblurring algorithm based on Very Deep Super Resolution ( VDSR ), in the hopes of providing solutions for the above mentioned matters, as well as forging more efficient and accurate tools for the animation industry.","PeriodicalId":49430,"journal":{"name":"Traitement Du Signal","volume":"218 5","pages":"0"},"PeriodicalIF":1.2000,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Automatic Depth Estimation and Background Blurring of Animated Scenes Based on Deep Learning\",\"authors\":\"Chao He, Yi Jia\",\"doi\":\"10.18280/ts.400539\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Animation technology enables more accurate depth estimation and background blurring of animated scenes as it can enhance the sense of reality of the vision and increase its depth, thus it has become a hot spot in relevant research and production these days. However, although deep learning has made significant progresses in many research fields, its application in depth estimation and background blurring of animated scenes is still facing a few challenges. Most available technologies are for real world images, not animations, so there are certain difficulties capturing the unique styles of animations and their details. This study proposes two technical schemes specifically designed for animated scenes: a depth estimation model based on DenseNet , and a deblurring algorithm based on Very Deep Super Resolution ( VDSR ), in the hopes of providing solutions for the above mentioned matters, as well as forging more efficient and accurate tools for the animation industry.\",\"PeriodicalId\":49430,\"journal\":{\"name\":\"Traitement Du Signal\",\"volume\":\"218 5\",\"pages\":\"0\"},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2023-10-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Traitement Du Signal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18280/ts.400539\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Traitement Du Signal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18280/ts.400539","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
Automatic Depth Estimation and Background Blurring of Animated Scenes Based on Deep Learning
Animation technology enables more accurate depth estimation and background blurring of animated scenes as it can enhance the sense of reality of the vision and increase its depth, thus it has become a hot spot in relevant research and production these days. However, although deep learning has made significant progresses in many research fields, its application in depth estimation and background blurring of animated scenes is still facing a few challenges. Most available technologies are for real world images, not animations, so there are certain difficulties capturing the unique styles of animations and their details. This study proposes two technical schemes specifically designed for animated scenes: a depth estimation model based on DenseNet , and a deblurring algorithm based on Very Deep Super Resolution ( VDSR ), in the hopes of providing solutions for the above mentioned matters, as well as forging more efficient and accurate tools for the animation industry.
期刊介绍:
The TS provides rapid dissemination of original research in the field of signal processing, imaging and visioning. Since its founding in 1984, the journal has published articles that present original research results of a fundamental, methodological or applied nature. The editorial board welcomes articles on the latest and most promising results of academic research, including both theoretical results and case studies.
The TS welcomes original research papers, technical notes and review articles on various disciplines, including but not limited to:
Signal processing
Imaging
Visioning
Control
Filtering
Compression
Data transmission
Noise reduction
Deconvolution
Prediction
Identification
Classification.