  This paper proposes Instruct 4D-to-4D that achieves 4D awareness and
spatial-temporal consistency for 2D diffusion models to generate high-quality
instruction-guided dynamic scene editing results. Traditional applications of
2D diffusion models in dynamic scene editing often result in inconsistency,
primarily due to their inherent frame-by-frame editing methodology. Addressing
the complexities of extending instruction-guided editing to 4D, our key insight
is to treat a 4D scene as a pseudo-3D scene, decoupled into two sub-problems:
achieving temporal consistency in video editing and applying these edits to the
pseudo-3D scene. Following this, we first enhance the Instruct-Pix2Pix (IP2P)
model with an anchor-aware attention module for batch processing and consistent
editing. Additionally, we integrate optical flow-guided appearance propagation
in a sliding window fashion for more precise frame-to-frame editing and
incorporate depth-based projection to manage the extensive data of pseudo-3D
scenes, followed by iterative editing to achieve convergence. We extensively
evaluate our approach in various scenes and editing instructions, and
demonstrate that it achieves spatially and temporally consistent editing
results, with significantly enhanced detail and sharpness over the prior art.
Notably, Instruct 4D-to-4D is general and applicable to both monocular and
challenging multi-camera scenes. Code and more results are available at
immortalco.github.io/Instruct-4D-to-4D.
