{"title":"具有热力学损失和解耦实例深度的单目三维物体检测","authors":"Gang Liu, Xiaoxiao Xie, Qingchen Yu","doi":"10.1080/09540091.2024.2316022","DOIUrl":null,"url":null,"abstract":"Monocular 3D detection is to obtain the 3D information of the object from the image. The mainstream methods mainly use L1 loss or L1-like loss to control the instance depth prediction. However, the...","PeriodicalId":50629,"journal":{"name":"Connection Science","volume":"18 1","pages":""},"PeriodicalIF":3.2000,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Monocular 3D object detection with thermodynamic loss and decoupled instance depth\",\"authors\":\"Gang Liu, Xiaoxiao Xie, Qingchen Yu\",\"doi\":\"10.1080/09540091.2024.2316022\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Monocular 3D detection is to obtain the 3D information of the object from the image. The mainstream methods mainly use L1 loss or L1-like loss to control the instance depth prediction. However, the...\",\"PeriodicalId\":50629,\"journal\":{\"name\":\"Connection Science\",\"volume\":\"18 1\",\"pages\":\"\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2024-02-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Connection Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/09540091.2024.2316022\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Connection Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/09540091.2024.2316022","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
Monocular 3D object detection with thermodynamic loss and decoupled instance depth
Monocular 3D detection is to obtain the 3D information of the object from the image. The mainstream methods mainly use L1 loss or L1-like loss to control the instance depth prediction. However, the...
期刊介绍:
Connection Science is an interdisciplinary journal dedicated to exploring the convergence of the analytic and synthetic sciences, including neuroscience, computational modelling, artificial intelligence, machine learning, deep learning, Database, Big Data, quantum computing, Blockchain, Zero-Knowledge, Internet of Things, Cybersecurity, and parallel and distributed computing.
A strong focus is on the articles arising from connectionist, probabilistic, dynamical, or evolutionary approaches in aspects of Computer Science, applied applications, and systems-level computational subjects that seek to understand models in science and engineering.