Figure 1. Our Carve3D algorithm steadily improves the 3D con-
sistency of a multi-view diffusion model and the resulting quality
of the NeRF and the mesh, without sacrificing its image-prompt
alignment, texture details, or realism. Here, we show 3 testing-
set results (in 3 rows, numbered as 1-3, separated by dotted lines)
from the finetuning process (epoch 0, 28, and 55 in 3 columns).
Each row includes the generated multi-view images (denoted as
MV), the reconstructed NeRF and extracted mesh (denoted as RM)
and the text prompt (denoted as TP). The inconsistencies in the
multi-view images, e.g. the facing direction of the shopping cart,
the position of the octopus arms, and the position of the pencils,
lead to artifacts in the NeRF and the mesh (highlighted in red).