Predicting the future by predicting the past
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Date
2018-01-01
Type of Work
Department
Computer Science and Electrical Engineering
Program
Computer Science
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Distribution Rights granted to UMBC by the author.
Access limited to the UMBC community. Item may possibly be obtained via Interlibrary Loan thorugh a local library, pending author/copyright holder's permission.
This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
Access limited to the UMBC community. Item may possibly be obtained via Interlibrary Loan thorugh a local library, pending author/copyright holder's permission.
This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
Abstract
Future prediction is an important problem in computer vision. We present a couple of intuitions about jointly predicting the future and past together and show that designing and adding novel loss terms based on these intuitions can improve the future prediction. We perform experiments with two totally different future prediction frameworks and show that both can benefit from our ideas.