MatSim Dataset and benchmark for one-shot visual materials and textures recognition

<strong>The MatSim Dataset and benchmark</strong> Synthetic dataset and real images benchmark for visual similarity recognition of materials and textures. MatSim: a synthetic dataset, a benchmark, and a method for computer vision-based recognition of similarities and transitions between materials and textures focusing on identifying any material under any conditions using one or a few examples (one-shot learning). Based on the paper: One-shot recognition of any material anywhere using contrastive learning with physics-based rendering <strong>Benchmark_MATSIM.zip: </strong>contain the benchmark made of real-world images as described in the paper <strong>Dataset Generation Scripts.zip: </strong>Contain the Blender (3.1) Python scripts used for generating the dataset<br> <br> <strong>MatSim_object_train_split_1,2,3.zip:</strong> Contain a subset of the synthetics dataset for images of CGI images materials on random objects as described in the paper. <strong>MatSim_Vessels_Train_1,2,3.zip </strong><strong>:</strong> Contain a subset of the synthetics dataset for images of CGI images materials inside transparent containers as described in the paper.<br> <br> <strong>*Note: these are subsets of the dataset; the full dataset can be found at:</strong><br> https://e1.pcloud.link/publink/show?code=kZIiSQZCYU5M4HOvnQykql9jxF4h0KiC5MX or<br> https://icedrive.net/s/A13FWzZ8V2aP9T4ufGQ1N3fBZxDF