datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
tactile-mnist-touch-real-single-t256-320x240Documentation is available at https://github.com/[REDACTED]/tactile-mnist/blob/main/doc/datasets.md#touch-datasets.
tactile-mnist-touch-syn-single-t32-64x64Documentation is available at https://github.com/[REDACTED]/tactile-mnist/blob/main/doc/datasets.md#touch-datasets.
tactile-mnist-touch-syn-single-t32-320x240Documentation is available at https://github.com/[REDACTED]/tactile-mnist/blob/main/doc/datasets.md#touch-datasets.
tactile-mnist-touch-starstruck-syn-single-t32-64x64Documentation is available at https://github.com/[REDACTED]/tactile-mnist/blob/main/doc/datasets.md#touch-datasets.
tactile-mnist-touch-real-single-t256-64x64Documentation is available at https://github.com/[REDACTED]/tactile-mnist/blob/main/doc/datasets.md#touch-datasets.
tactile-mnist-touch-starstruck-syn-single-t32-320x240Documentation is available at https://github.com/[REDACTED]/tactile-mnist/blob/main/doc/datasets.md#touch-datasets.
TextureBench-3DGS
TextureBench-3DGS
Note. This is an anonymised copy of the benchmark released for the double-blind review process. It contains no author
information; the full release with attribution, licence details and accompanying code will be published after the review.
TextureBench-3DGS is a benchmark of 28 real outdoor scenes with dense natural texture (gravel, grass, leaves, brick, concrete,
tiles, foliage), each captured as a multi-view photo set suitable for 3D Gaussian Splatting… See the full description on the dataset page: https://huggingface.co/datasets/anonymous-user-submission/TextureBench-3DGS.