{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/semi-recurrent-cnn-based-vae-gan-for","title":"Semi-Recurrent CNN-based VAE-GAN for Sequential Data Generation","arxiv_id":"1806.00509","date":"2018-06-01","proceeding":null,"authors":["Mohammad Akbari","Jie Liang"],"abstract":"A semi-recurrent hybrid VAE-GAN model for generating sequential data is\nintroduced. In order to consider the spatial correlation of the data in each\nframe of the generated sequence, CNNs are utilized in the encoder, generator,\nand discriminator. The subsequent frames are sampled from the latent\ndistributions obtained by encoding the previous frames. As a result, the\ndependencies between the frames are maintained. Two testing frameworks for\nsynthesizing a sequence with any number of frames are also proposed. The\npromising experimental results on piano music generation indicates the\npotential of the proposed framework in modeling other sequential data such as\nvideo.","url_abs":"http://arxiv.org/abs/1806.00509v1","url_pdf":"http://arxiv.org/pdf/1806.00509v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"semi-recurrent-cnn-based-vae-gan-for","repo_url":"https://github.com/makbari7/SR-CNN-VAE-GAN","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"music-generation","task_name":"Music Generation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}