Viewpoint Estimation-Insights & Model
It addresses viewpoint estimation for computer vision applications, presenting an incremental improvement with specific gains.
The paper tackles viewpoint estimation of objects in images by proposing a CNN that jointly handles detection, classification, and viewpoint estimation, improving state-of-the-art results by 9.8%.
This paper addresses the problem of viewpoint estimation of an object in a given image. It presents five key insights that should be taken into consideration when designing a CNN that solves the problem. Based on these insights, the paper proposes a network in which (i) The architecture jointly solves detection, classification, and viewpoint estimation. (ii) New types of data are added and trained on. (iii) A novel loss function, which takes into account both the geometry of the problem and the new types of data, is propose. Our network improves the state-of-the-art results for this problem by 9.8%.