BrushNet

GeM-NR: Training-free multi-view editing for nonrigid 3D scene changes

GeM-NR is a training-free method for multi-view consistent image editing that handles nonrigid edits — changes that substantially alter scene geometry and appearance — a capability that existing methods largely lack. Given an anchor image edited by a backbone model (FLUX, Qwen, or BrushNet) and an unedited query image, the method propagates the edit consistently across viewpoints via depth estimation, point-cloud alignment, projection, and conditioned refinement. The authors report state-of-the-art performance on edit quality and geometric/photometric consistency across multiple views, including generation of 3D representations of edited scenes.