Position Estimation of Camera Based on Unsupervised Learning
원문 초록
It is an exciting task to recover the scene's 3d-structure and camera pose from the video sequence. Most of the current solutions divide it into two parts, monocular depth recovery and camera pose estimation. The monocular depth recovery is often studied as an independent part, and a better depth estimation is used to solve the pose. While camera pose is still estimated by traditional SLAM (Simultaneous Localization And Mapping) methods in most cases. The use of unsupervised method for monocular depth recovery and pose estimation has benefited from the study of [1] and achieved good results. In this paper, we improve the method of [1]. Our emphasis is laid on the improvement of the idea and related theory, introducing a more reasonable inter frame constraints and finally synthesize the camera trajectory with inter frame pose estimation in the unified world coordinate system. And our results get better performance.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
$π^3$: Scalable Permutation-Equivariant Visual Geometry Learning
Voyager: Long-Range and World-Consistent Video Diffusion for Explorable 3D Scene Generation
Efficient Calisthenics Skills Classification through Foreground Instance Selection and Depth Estimation
SpatialTrackerV2: 3D Point Tracking Made Easy
SupeRANSAC: One RANSAC to Rule Them All
Recollection from Pensieve: Novel View Synthesis via Learning from Uncalibrated Videos
토론
이 논문과 연결된 포럼 글이 아직 없습니다.