# Instruct 4D-to-4D: Editing 4D Scenes as Pseudo-3D Scenes Using 2D Diffusion

**Authors:** Linzhan Mou, Jun-Kun Chen, Yu-Xiong Wang  
**arXiv:** [2406.09402](https://arxiv.org/abs/2406.09402)  
**Date:** 2024-06-13  
**Summary page:** https://www.summarizepaper.com/en/paper/2406.09402v1/

## Key points

- Authors introduce a novel approach for achieving spatial-temporal consistency in dynamic scene editing using instruction-guided techniques
- Proposal to treat a 4D scene as a pseudo-3D scene and address temporal consistency and editing application as main sub-problems
- Augmentation of Instruct-Pix2Pix (IP2P) model with anchor-aware attention module for batch processing and consistent editing
- Integration of optical flow-guided appearance propagation in sliding window fashion for precise frame-to-frame editing
- Incorporation of depth-based projection techniques to manage data associated with pseudo-3D scenes
- Utilization of iterative editing processes for convergence and result refinement
- Extensive evaluations show that Instruct 4D-to-4D produces consistent outcomes with improved detail compared to existing methods, applicable to monocular scenes and multi-camera setups

## Summary

In their paper titled "Instruct 4D-to-4D: Editing 4D Scenes as Pseudo-3D Scenes Using 2D Diffusion," authors Linzhan Mou, Jun-Kun Chen, and Yu-Xiong Wang introduce a novel approach for achieving spatial-temporal consistency in dynamic scene editing by utilizing instruction-guided techniques. The traditional use of 2D diffusion models in this context often leads to inconsistencies due to their frame-by-frame editing methodology. To address this challenge and extend instruction-guided editing to 4D scenes, the authors propose treating a 4D scene as a pseudo-3D scene and divide it into two main sub-problems: ensuring temporal consistency in video editing and applying these edits to the pseudo-3D scene. To enhance their proposed method, the authors first augment the Instruct-Pix2Pix (IP2P) model with an anchor-aware attention module for batch processing and consistent editing. They also integrate optical flow-guided appearance propagation in a sliding window fashion for more precise frame-to-frame editing. Depth-based projection techniques are incorporated to manage the extensive data associated with pseudo-3D scenes. The authors further employ iterative editing processes to achieve convergence and refine the results. Extensive evaluations of their approach across various scenes and editing instructions demonstrate that Instruct 4D-to-4D produces spatially and temporally consistent outcomes with significantly improved detail and sharpness compared to existing methods. Importantly, the proposed technique is versatile and applicable not only to monocular scenes but also challenging multi-camera setups. For those interested in exploring further details, code implementation and additional results can be accessed at immortalco.github.io/Instruct-4D-to-4D. Overall, this paper presents a comprehensive framework for enhancing dynamic scene editing through instruction-guided approaches, showcasing its effectiveness in achieving high-quality results in both spatial and temporal domains.