reviews: 
Comments: This paper proposes a novel method for synthesizing photorealistic talking portraits from a single source image coupled with either a speech signal or a driving facial video. The method generates a 3D avatar from the source image and then animates it based on the speech signal or the driving video. Apart from the talking head synthesis, the method pays attention in the realistic synthesis of torso movements and backgrounds. Regarding the module of 3D face reconstruction, the method adopts an image to plane model. Regarding the module of animation, the method introduces a novel facial motion adapter. The paper presents detailed experiments (qualitative and quantitative evaluations, user studies and ablation studies) that show the advantages and promising performance of the proposed method.
Strengths: + The proposed method is interesting and its pipeline has sufficient novelty, especially in terms of the combination of the large-scale image-to-plane backbone, the motion adapter and the Head-Torso-Background Super-Resolution model, which results in particularly realistic results. 

+ The paper includes an in-depth experimental evaluation that provides sound evidence about the promising results of the proposed method. In more detail, the proposed method is compared with several recent SOTA methods (despite the fact that some additional methods should have been included - see comments below). The evaluation includes qualitative and quantitative comparisons, as well as user studies that are important to judge the perceived quality of the results. The ablation studies are also detailed and clearly show the importance and benefits of the different modules of the pipeline. Finally, the supplementary videos are informative and help to appreciate the visual quality of the results, as well as the advantages of the proposed method over the previous SOTA techniques.
Weaknesses: - The paper has omitted citing some important related methods of the field: 

J. S. Chung, A. Jamaludin, and A. Zisserman, “You said that?” in BMVC, 2017.

Ye, Z., Xia, M., Yi, R., Zhang, J., Lai, Y.-K., Huang, X., et al. (2022). Audio-driven talking face video generation with dynamic convolution kernels. IEEE Transactions on Multimedia.

In addition, the method is based on the projected normalized coordinate code (PNCC) representation but it has not cited one of the most important works of the field that is also based on the same representation:

Kim, H., Garrido, P., Tewari, A., Xu, W., Thies, J., Niessner, M., Pérez, P., Richardt, C., Zollhöfer, M. and Theobalt, C., 2018. Deep video portraits. ACM transactions on graphics (TOG), 37(4), pp.1-14.

Also, the method supports the conditioning of the animation based on a speech audio signal but it does not cite another important and seminal work of the field that does something similar: 

Kim, H., Elgharib, M., Zollhöfer, M., Seidel, H.P., Beeler, T., Richardt, C. and Theobalt, C., 2019. Neural style-preserving visual dubbing. ACM Transactions on Graphics (TOG), 38(6), pp.1-13.


- In the part of the Audio-driven talking face generation of the experimental comparisons, some additional recent works should have been added in the comparisons. For example, the paper should have cited and included in the comparisons the following methods that solve the same problem:

Yi, R., Ye, Z., Zhang, J., Bao, H. and Liu, Y.J., 2020. Audio-driven talking face video generation with learning-based personalized head pose. arXiv preprint arXiv:2002.10137.

Yao, S., Zhong, R., Yan, Y., Zhai, G. and Yang, X., 2022. DFA-NeRF: Personalized talking head generation via disentangled face attributes neural rendering. arXiv preprint arXiv:2201.00791.
Recommendation: 10: strong accept, should be highlighted at the conference
Reviewer confidence: 4: You are confident in your assessment, but not absolutely certain. It is unlikely, but not impossible, that you did not understand some parts of the submission or that you are unfamiliar with some pieces of related work.
Soundness/correctness: 4 excellent
Clarity: 3 good