Tracking by 3D Model Estimation of Unknown Objects in Videos
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F23%3A00371803" target="_blank" >RIV/68407700:21230/23:00371803 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/ICCV51070.2023.01295" target="_blank" >https://doi.org/10.1109/ICCV51070.2023.01295</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICCV51070.2023.01295" target="_blank" >10.1109/ICCV51070.2023.01295</a>
Alternative languages
Result language
angličtina
Original language name
Tracking by 3D Model Estimation of Unknown Objects in Videos
Original language description
Most model-free visual object tracking methods formulate the tracking task as object location estimation given by a 2D segmentation or a bounding box in each video frame. We argue that this representation is limited and instead propose to guide and improve 2D tracking with an explicit object representation, namely the textured 3D shape and 6DoF pose in each video frame. Our representation tackles a complex long-term dense correspondence problem between all 3D points on the object for all video frames, including frames where some points are invisible. To achieve that, the estimation is driven by re-rendering the input video frames as well as possible through differentiable rendering, which has not been used for tracking before. The proposed optimization minimizes a novel loss function to estimate the best 3D shape, texture, and 6DoF pose. We improve the state-of-the-art in 2D segmentation tracking on three different datasets with mostly rigid objects.
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
<a href="/en/project/EF16_019%2F0000765" target="_blank" >EF16_019/0000765: Research Center for Informatics</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
ICCV2023: Proceedings of the International Conference on Computer Vision
ISBN
979-8-3503-0719-1
ISSN
1550-5499
e-ISSN
2380-7504
Number of pages
11
Pages from-to
14040-14050
Publisher name
IEEE
Place of publication
Piscataway
Event location
Paris
Event date
Oct 2, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001169499006047