The field of 3D image synthesis and novel view generation is rapidly advancing, with a focus on developing more accurate and efficient methods for generating realistic images and videos. Recent research has explored the use of diffusion-based models, transformers, and warping-guided techniques to improve the quality and consistency of generated images. These approaches have shown significant improvements over traditional methods, particularly in handling complex scenes and viewpoints. Notably, the development of modular and symmetry-aware designs is becoming increasingly important for addressing the limitations of current models. Overall, the field is moving towards more robust and generalizable methods for 3D image synthesis and novel view generation. Noteworthy papers include: VectorSynth, which introduces a diffusion-based framework for fine-grained satellite image synthesis. WarpGAN, which proposes a warping-and-inpainting strategy for 3D GAN inversion. DT-NVS, which presents a 3D-aware diffusion model for generalized novel view synthesis.