Sub-frame Appearance and 6D Pose Estimation of Fast Moving Objects
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Abstract (arXiv)
We propose a novel method that tracks fast moving objects, mainly non-uniform spherical, in full 6 degrees of freedom, estimating simultaneously their 3D motion trajectory, 3D pose and object appearance changes with a time step that is a fraction of the video frame exposure time. The sub-frame object localization and appearance estimation allows realistic temporal super-resolution and precise shape estimation. The method, called TbD-3D (Tracking by Deblatting in 3D) relies on a novel reconstruction algorithm which solves a piece-wise deblurring and matting problem. The 3D rotation is estimated by minimizing the reprojection error. As a second contribution, we present a new challenging dataset with fast moving objects that change their appearance and distance to the camera. High speed camera recordings with zero lag between frame exposures were used to generate videos with different frame rates annotated with ground-truth trajectory and pose.
Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). First posted on arXiv 25 Nov 2019.
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Citing papers per year: 2021: 3; 2022: 1; 2023: 1; 2024: 1; 2025: 3; 2026: 1.
10 papers.
- 2022DGECN: A Depth-Guided Edge Convolutional Network for End-to-End 6D Pose Estimationcited by 12
- 2021Motion-from-Blur: 3D Shape and Motion Estimation of Motion-blurred Objects in Videoscited by 11
- 2021Shape from Blur: Recovering Textured 3D Shape and Motion of Fast Moving Objectscited by 10
- 2021Finding Geometric Models by Clustering in the Consensus Spacecited by 8
- 2023Human from Blur: Human Pose Tracking from Blurry Imagescited by 3
- 2025Benchmarking EfficientTAM on FMO datasetscited by 1
- 2025BlurBall: Joint Ball and Motion Blur Estimation for Table Tennis Ball Trackingcited by 1
- 2024Retrieval Robust to Object Motion Blurcited by 0
- 2025Benchmarking SAM2-based Trackers on FMOXcited by 0
- 2026Recovering 3D Shapes from Ultra-Fast Motion-Blurred Imagescited by 0
- 2026Recovering 3D Shapes from Ultra-Fast Motion-Blurred Images8 Feb 2026
- 2025Benchmarking SAM2-based Trackers on FMOX10 Dec 2025
- 2025BlurBall: Joint Ball and Motion Blur Estimation for Table Tennis Ball Tracking22 Sep 2025
- 2025Benchmarking EfficientTAM on FMO datasets8 Sep 2025
- 2024Retrieval Robust to Object Motion Blur27 Apr 2024
- 2023Human from Blur: Human Pose Tracking from Blurry Images30 Mar 2023
- 2022DGECN: A Depth-Guided Edge Convolutional Network for End-to-End 6D Pose Estimation21 Apr 2022
- 2021Motion-from-Blur: 3D Shape and Motion Estimation of Motion-blurred Objects in Videos29 Nov 2021
- 2021Shape from Blur: Recovering Textured 3D Shape and Motion of Fast Moving Objects16 Jun 2021
- 2021Finding Geometric Models by Clustering in the Consensus Space25 Mar 2021