View 3D Consistency

View 3D consistency in computer vision focuses on ensuring that representations of 3D scenes from multiple viewpoints are coherent and accurate. Current research emphasizes improving the robustness and quality of 3D scene reconstruction using neural radiance fields (NeRFs) and diffusion models, often addressing challenges like sparse views, low-quality input images, and the need for efficient editing capabilities. These advancements are crucial for applications such as high-fidelity 3D modeling, realistic image editing, and unsupervised 3D object segmentation, ultimately improving the accuracy and efficiency of 3D scene understanding. The development of novel consistency modules and loss functions within these frameworks is a key area of ongoing investigation.