Flying Chairs

doi:doi:10.57702/9phl0l35

Flying Chairs

The dataset used in the paper is not explicitly described, but it is mentioned that the authors applied their approach to the challenging problem of optical flow estimation and empirically validated it against state-of-the-art CNN-based solutions trained from scratch and tested on large optical flow datasets.

BibTex:

@dataset{Sean_I_Young_and_William_M_Wells_and_Yaël_Balbastre_and_Adrian_V_Dalca_and_Bruce_Fischl_and_Juan_Eugenio_Iglesias_2024,
    abstract = {The dataset used in the paper is not explicitly described, but it is mentioned that the authors applied their approach to the challenging problem of optical flow estimation and empirically validated it against state-of-the-art CNN-based solutions trained from scratch and tested on large optical flow datasets.},
    author = {Sean I. Young and William M. Wells and Yaël Balbastre and Adrian V. Dalca and Bruce Fischl and Juan Eugenio Iglesias},
    doi = {10.57702/9phl0l35},
    institution = {No Organization},
    keyword = {'CNN-based solutions', 'Image Registration', 'Optical Flow Estimation', 'computer vision', 'dense pixel-wise estimation', 'low-power', 'mobile', 'motion estimation', 'optical flow'},
    month = {dec},
    publisher = {TIB},
    title = {Flying Chairs},
    url = {https://service.tib.eu/ldmservice/dataset/flying-chairs},
    year = {2024}
}