This repository stores the preprocessed data for paper:
SignDiff: Learning Diffusion Models for American Sign Language Production
Note: We're going to start a company, and the code is not going to be public.
After preprocessing How2Sign dataset, the condensed data set obtained is as follows:
It can be used in the training of ASL production models.
Note: Because I later processed more data, the link above is four times the size of the one in the paper and is the result of the full How2Sign processing.
After preprocessing Phoenix-14T dataset, the condensed data set obtained is as follows:
It can be used in the training of GSL production models.
After preprocessing How2Sign dataset, the condensed data set obtained is as follows:
It can be used for the diffusion model training of pose2video in sign language. (Based on ControlNet)
After preprocessing How2Sign dataset, the condensed data set obtained is as follows:
It can be used for the GAN model training of pose2video in sign language. (Based on Vid2Vid)
Our pre-processing tools: the data cleansing tool and the three-step 2Dto3D tool.
Stay tuned. The data above should be sufficient for the time being.
@misc{fang2024signllm, title={SignLLM: Sign Languages Production Large Language Models}, author={Sen Fang and Lei Wang and Ce Zheng and Yapeng Tian and Chen Chen}, year={2024}, eprint={2405.10718}, archivePrefix={arXiv}, primaryClass={cs.CV} } @misc{fang2023signdiff, title={SignDiff: Learning Diffusion Models for American Sign Language Production}, author={Sen Fang and Chunyu Sui and Xuedong Zhang and Yapeng Tian}, year={2023}, eprint={2308.16082}, archivePrefix={arXiv}, primaryClass={cs.CV} }