The field of 3D human reconstruction and animation is rapidly advancing, with a focus on developing more efficient, accurate, and realistic methods. Recent research has explored the use of end-to-end networks, anatomy shaping, and twins negotiating reconstruction to improve the quality of 3D human avatars. Additionally, there has been a significant emphasis on developing methods for real-time full-body pose estimation, dynamic human neural fields, and compositional TV show reconstruction. These advances have the potential to revolutionize applications such as AR/VR, virtual try-ons, and video production. Noteworthy papers in this area include Unify3D, which introduces a novel paradigm for holistic 3D human reconstruction, and SSD-Poser, which proposes a lightweight and efficient model for robust full-body motion estimation. HumMorph is also noteworthy for its ability to render dynamic human bodies with explicit pose control from few views.