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Although many progressive algorithms exist for efficient encoding of connectivity and geometry, none of these techniques consider the color data in spite of its considerable size. Based on the powerful progressive algorithm from Alliez and Desbrun [All01a], we propose two extensions for progressive ...
In recent years, significant advancements have been made in the field of image denoising, leading to the emergence of a plethora of sophisticated algorithms. Broadly, these algorithms can be categorized into two primary groups: the conventional methods reliant on artificial features, and those anchored...
For more compute vision algorithms, please refer toOpenCVofficial site Deep Learning -- FromWiki: Deep learning (also known as deep structured learning or hierarchical learning) is part of a broader family of machine learning methods based on learning data representations, as opposed to task-specifi...
Our experiments demonstrate that ProFeat outperforms previous state-of-the-art algorithms in terms of clustering accuracy, and that our ensemble-based approach further improves clustering accuracy. 2. Related work Clustering has been extensively studied over decades in the machine learning and computer ...
Most existing person Re-Identification (Re-ID) algorithms require abundant labeled data from paired non-overlapping camera views in the fully supervised scenario. However, the fully supervised Re-ID suffers from the limited availability of labeled training samples due to the sharply increased cost of...
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The pre-trained generator is then combined with various approaches like semantic inpainting or geostatistical algorithms. However, Ruffino et al. (2020) took a different approach by directly conditioning hard data to the GAN, allowing the network to learn to generate realizations constrained to the ...