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Current visual generation methods can produce high quality videos guided by texts.
Chung, J.S., Zisserman, A.: Lip reading in the wild. In: ACCV (2016)
2016
Earlier work this paper cites.
Chung, J.S., Zisserman, A.: Out of time: automated lip sync in the wild. In: ACCV Workshop (2016)
2016
Earlier work this paper cites.
Owens, A., Isola, P., McDermott, J., Torralba, A., Adelson, E.H., Freeman, W.T.: Visually indicated sounds. In: CVPR (2016)
2016
Earlier work this paper cites.
Gemmeke, J.F., Ellis, D.P.W., Freedman, D., Jansen, A., Lawrence, W., Moore, R.C., Plakal, M., Ritter, M.: Audio set: An ontology and human-labeled dataset for audio events. In: Proc. IEEE ICASSP 2017 (2017)
2017
Earlier work this paper cites.
Heusel, M., Ramsauer, H., Unterthiner, T., Nessler, B., Hochreiter, S.: Gans trained by a two time-scale update rule converge to a local nash equilibrium. In: Advances in Neural Information Processing Systems (2017)
2017
Earlier work this paper cites.
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, L., Polosukhin, I.: Attention is all you need. In: NeurIPS (2017)
2017
Earlier work this paper cites.
Brock, A., Donahue, J., Simonyan, K.: Large scale gan training for high fidelity natural image synthesis. In: ICLR (2019)
2019
Earlier work this paper cites.
Chung, S.W., Chung, J.S., Kang, H.G.: Perfect match: Improved cross-modal embeddings for audio-visual synchronisation. In: ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (2019)
2019
Earlier work this paper cites.
Tsuchida, S., Fukayama, S., Hamasaki, M., Goto, M.: Aist dance video database: Multi-genre, multi-dancer, and multi-camera database for dance information processing. In: Proceedings of the 20th International Society for Music Information Retrieval Conference, ISMIR 2019. Delft, Netherlands (Nov 2019)
2019
Earlier work this paper cites.
Unterthiner, T., van Steenkiste, S., Kurach, K., Marinier, R., Michalski, M., Gelly, S.: Towards accurate generative models of video: A new metric & challenges. In: arXiv (2019)
2019
Earlier work this paper cites.
Zhou, H., Liu, Y., Liu, Z., Luo, P., Wang, X.: Talking face generation by adversarially disentangled audio-visual representation. In: AAAI Conference on Artificial Intelligence (AAAI) (2019)
2019
Earlier work this paper cites.
Chen, H., Xie, W., Vedaldi, A., Zisserman, A.: Vggsound: A large-scale audio-visual dataset. In: ICASSP (2020)
2020
Earlier work this paper cites.
Ho, J., Jain, A., Abbeel, P.: Denoising diffusion probabilistic models. In: NeurIPS (2020)
2020
Earlier work this paper cites.
Bain, M., Nagrani, A., Varol, G., Zisserman, A.: Frozen in time: A joint video and image encoder for end-to-end retrieval. In: IEEE International Conference on Computer Vision (2021)
2021
Earlier work this paper cites.
Chen, H., Xie, W., Afouras, T., Nagrani, A., Vedaldi, A., Zisserman, A.: Audio-visual synchronization in the wild. In: Proceedings of the British Machine Vision Conference (BMVC) (2021)
2021
Earlier work this paper cites.
Dhariwal, P., Nichol, A.: Diffusion models beat gans on image synthesis. In: NeurIPS (2021)
2021
Earlier work this paper cites.
Li, R., Yang, S., Ross, D.A., Kanazawa, A.: Learn to dance with aist++: Music conditioned 3d dance generation. In: ICCV (2021)
2021
Earlier work this paper cites.
Pedro Morgado, Ishan Misra, N.V.: Robust audio-visual instance discrimination. In: Computer Vision and Pattern Recognition (CVPR), IEEE/CVF Conf. on (2021)
2021
Cited alongside, same era.
Radford, A., Kim, J.W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., Krueger, G., Sutskever, I.: Learning transferable visual models from natural language supervision. In: ICML (2021)
2021
Cited alongside, same era.
Song, J., Meng, C., Ermon, S.: Denoising diffusion implicit models. In: ICLR (2021)
2021
Cited alongside, same era.
Xu, H., Ghosh, G., Huang, P.Y., Okhonko, D., Aghajanyan, A., Metze, F., Zettlemoyer, L., Feichtenhofer, C.: Videoclip: Contrastive pre-training for zero-shot video-text understanding. In: EMNLP (2021)
2021
Cited alongside, same era.
Hertz, A., Mokady, R., Tenenbaum, J., Aberman, K., Pritch, Y., Cohen-Or, D.: Prompt-to-prompt image editing with cross attention control. In: ICLR (2023)
2023
Later among the works it cites.
Jeong, Y., Ryoo, W., Lee, S., Seo, D., Byeon, W., Kim, S., Kim, J.: The power of sound (tpos): Audio reactive video generation with stable diffusion. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 7822–7832 (2023)
2023
Later among the works it cites.
Khachatryan, L., Movsisyan, A., Tadevosyan, V., Henschel, R., Wang, Z., Navasardyan, S., Shi, H.: Text2video-zero: Text-to-image diffusion models are zero-shot video generators. In: ICCV (2023)
2023
Later among the works it cites.
Lee, S., Kong, C., Jeon, D., Kwak, N.: Aadiff: Audio-aligned video synthesis with text-to-image diffusion. In: CVPR Workshop on Content Generation (2023)
2023
Later among the works it cites.
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Zhou, H., Sun, Y., Wu, W., Loy, C.C., Wang, X., Liu, Z.: Pose-controllable talking face generation by implicitly modularized audio-visual representation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2021)
2021
Cited alongside, same era.
Ho, J., Salimans, T.: Classifier-free diffusion guidance. In: NeurIPS Workshop on Deep Generative Models and Downstream Applications (2022)
2022
Cited alongside, same era.
Iashin, V., Xie, W., Rahtu, E., Zisserman, A.: Sparse in space and time: Audio-visual synchronisation with trainable selectors. In: British Machine Vision Conference (BMVC) (2022)
2022
Cited alongside, same era.
Lee, S.H., Oh, G., Byeon, W., Bae, J., Kim, C., Ryoo, W.J., Yoon, S.H., Kim, J., Kim, S.: Sound-guided semantic video generation. In: ECCV (2022)
2022
Cited alongside, same era.
Park, S.J., Kim, M., Hong, J., Choi, J., Ro, Y.M.: Synctalkface: Talking face generation with precise lip-syncing via audio-lip memory. In: AAAI Conference on Artificial Intelligence (AAAI) (2022)
2022
Cited alongside, same era.
Ramesh, A., Dhariwal, P., Nichol, A., Chu, C., Chen, M.: Hierarchical text-conditional image generation with clip latents. In: arXiv (2022)
2022
Cited alongside, same era.
Rombach, R., Blattmann, A., Lorenz, D., Esser, P., Ommer, B.: High-resolution image synthesis with latent diffusion models. In: CVPR (2022)
2022
Cited alongside, same era.
Schuhmann, C., Beaumont, R., Vencu, R., Gordon, C., Wightman, R., Cherti, M., Coombes, T., Katta, A., Mullis, C., Wortsman, M., Schramowski, P., Kundurthy, S., Crowson, K., Schmidt, L., Kaczmarczyk, R., Jitsev, J.: Laion-5b: An open large-scale dataset for training next generation image-text models. In: NeurIPS (2022)
2022
Cited alongside, same era.
Li, Y., Liu, H., Wu, Q., Mu, F., Yang, J., Gao, J., Li, C., Lee, Y.J.: Gligen: Open-set grounded text-to-image generation. In: CVPR (2023)
2023
Later among the works it cites.
Luo, S., Yan, C., Hu, C., Zhao, H.: Diff-foley: Synchronized video-to-audio synthesis with latent diffusion models. In: NeurIPS (2023)
2023
Later among the works it cites.
Mokady, R., Hertz, A., Aberman, K., Pritch, Y., Cohen-Or, D.: Null-text inversion for editing real images using guided diffusion models. In: CVPR (2023)
2023
Later among the works it cites.
Ruan, L., Ma, Y., Yang, H., He, H., Liu, B., Fu, J., Yuan, N.J., Jin, Q., Guo, B.: Mm-diffusion: Learning multi-modal diffusion models for joint audio and video generation. In: CVPR (2023)
2023
Later among the works it cites.
Sung-Bin, K., Senocak, A., Ha, H., Owens, A., Oh, T.H.: Sound to visual scene generation by audio-to-visual latent alignment. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2023)
2023
Later among the works it cites.
Tang, Z., Yang, Z., Zhu, C., Zeng, M., Bansal, M.: Any-to-any generation via composable diffusion. In: Thirty-seventh Conference on Neural Information Processing Systems (2023), https://openreview.net/forum?id=2EDqbSCnmF
2023
Later among the works it cites.
Wang, J., Yuan, H., Chen, D., Zhang, Y., Wang, X., Zhang, S.: Modelscope text-to-video technical report (2023)
2023
Later among the works it cites.
2023
Later among the works it cites.
2023
Later among the works it cites.
Yariv, G., Gat, I., Benaim, S., Wolf, L., Schwartz, I., Adi, Y.: Diverse and aligned audio-to-video generation via text-to-video model adaptation (2023)
2023
Later among the works it cites.
Ye, Z., Jiang, Z., Ren, Y., Liu, J., He, J., Zhao, Z.: Geneface: Generalized and high-fidelity audio-driven 3d talking face synthesis. In: ICLR (2023)
2023
Later among the works it cites.
Zhang, L., Rao, A., Agrawala, M.: Adding conditional control to text-to-image diffusion models. In: IEEE International Conference on Computer Vision (ICCV) (2023)
2023
Later among the works it cites.
Ng, E., Romero, J., Bagautdinov, T., Bai, S., Darrell, T., Kanazawa, A., Richard, A.: From audio to photoreal embodiment: Synthesizing humans in conversations. In: ArXiv (2024)
2024
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