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Recent one image to 3D generation methods commonly adopt Score DistillationSampling (SDS). Despite the impressive results, there are multiple deficienciesincluding multi-view inconsistency, over-saturated and over-smoothed textures,as well as the slow generation speed. To address these deficiencies, we presentRepaint123 to alleviate multi-view bias as well as texture degradation andspeed up the generation process. The core idea is to combine the powerful imagegeneration capability of the 2D diffusion model and the texture alignmentability of the repainting strategy for generating high-quality multi-viewimages with consistency. We further propose visibility-aware adaptiverepainting strength for overlap regions to enhance the generated image qualityin the repainting process. The generated high-quality and multi-view consistentimages enable the use of simple Mean Square Error (MSE) loss for fast 3Dcontent generation. We conduct extensive experiments and show that our methodhas a superior ability to generate high-quality 3D content with multi-viewconsistency and fine textures in 2 minutes from scratch. Our project page isavailable at https://pku-yuangroup.github.io/repaint123/.

Repaint123: Fast and High-quality One Image to 3D Generation with Progressive Controllable 2D Repainting