  Recent advancements in text-to-3D generation have demonstrated the ability to
generate high quality 3D assets. However while generating animals these methods
underperform, often portraying inaccurate anatomy and geometry. Towards
ameliorating this defect, we present C3DAG, a novel pose-Controlled text-to-3D
Animal Generation framework which generates a high quality 3D animal consistent
with a given pose. We also introduce an automatic 3D shape creator tool, that
allows dynamic pose generation and modification via a web-based tool, and that
generates a 3D balloon animal using simple geometries. A NeRF is then
initialized using this 3D shape using depth-controlled SDS. In the next stage,
the pre-trained NeRF is fine-tuned using quadruped-pose-controlled SDS. The
pipeline that we have developed not only produces geometrically and
anatomically consistent results, but also renders highly controlled 3D animals,
unlike prior methods which do not allow fine-grained pose control.
