Single-Image Deblurring, Trajectory and Shape Recovery of Fast Moving Objects with Denoising Diffusion Probabilistic Models
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F24%3A00376639" target="_blank" >RIV/68407700:21230/24:00376639 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/WACV57701.2024.00671" target="_blank" >http://dx.doi.org/10.1109/WACV57701.2024.00671</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/WACV57701.2024.00671" target="_blank" >10.1109/WACV57701.2024.00671</a>
Alternative languages
Result language
angličtina
Original language name
Single-Image Deblurring, Trajectory and Shape Recovery of Fast Moving Objects with Denoising Diffusion Probabilistic Models
Original language description
Blurry appearance of fast moving objects in video frames was successfully used to reconstruct the object appearance and motion in both 2D and 3D domains. The proposed method addresses the novel, severely ill-posed, task of single-image fast moving object deblurring, shape, and trajectory recovery--previous approaches require at least three consecutive video frames. Given a single image, the method outputs the object 2D appearance and position in a series of sub-frames as if captured by a high-speed camera (ie temporal super-resolution). The proposed SI-DDPM-FMO method is trained end-to-end on a synthetic dataset with various moving objects, yet it generalizes well to real-world data from several publicly available datasets. SI-DDPM-FMO performs similarly to or better than recent multi-frame methods and a carefully designed baseline method.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
ISBN
979-8-3503-1892-0
ISSN
2472-6737
e-ISSN
2642-9381
Number of pages
10
Pages from-to
6843-6852
Publisher name
IEEE
Place of publication
Piscataway
Event location
Waikoloa, HI, USA
Event date
Jan 4, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001222964606095