• G1NDiff: Reprojection-Aware One-Step Diffusion for Fast Multi-View Consistent 3D Scene Editing • G1NDiff: A one-step GAN-based image editing model that preserves consistency across successive edits. • Occlusion-aware Reprojection: An algorithm that transforms a single image into a pair of conditioning-target views. • Multi-stage Pipeline: A scene editing pipeline where G1NDiff is applied for gradually editing all views of a given 3D scene. • State of the art performance on 2DGS scenes, with higher MEt3R consistency and over 10× speedup.

Advances in NERFs have allowed for 3D scene reconstructions and novel view synthesis. Yet, efficiently editing these representations while retaining photo realism is an emerging challenge. Recent methods face three primary limitations: they're slow for interactive use, lack precision at object boundaries, and struggle to ensure multi-view consistency. We introduce IReNe to address these limitations, enabling swift, near real-time color editing in NeRF. Leveraging a pre-trained NeRF model and a single training image with user-applied color edits, IReNe swiftly adjusts network parameters in seconds. This adjustment allows the model to generate new scene views, accurately representing the color changes from the training image while also controlling object boundaries and view-specific effects. Object boundary control is achieved by integrating a trainable segmentation module into the model. The process gains efficiency by retraining only the weights of the last network layer. We observed that neurons in this layer can be classified into those responsible for view-dependent appearance and those contributing to diffuse appearance. We introduce an automated classification approach to identify these neuron types and exclusively fine-tune the weights of the diffuse neurons. This further accelerates training and ensures consistent color edits across different views. A thorough validation on a new dataset, with edited object colors, shows significant quantitative and qualitative advancements over competitors, accelerating speeds by 5x to 500x.