arXiv:2010.04949
공식 코드 · Papers with Code
Image Generation With Neural Cellular Automatas
원문 초록
In this paper, we propose a novel approach to generate images (or other artworks) by using neural cellular automatas (NCAs). Rather than training NCAs based on single images one by one, we combined the idea with variational autoencoders (VAEs), and hence explored some applications, such as image restoration and style fusion. The code for model implementation is available online.
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Forward-only Diffusion Probabilistic Models
RestoreVAR: Visual Autoregressive Generation for All-in-One Image Restoration
NTIRE 2025 challenge on Text to Image Generation Model Quality Assessment
MFGDiffusion: Mask-Guided Smoke Synthesis for Enhanced Forest Fire Detection
Implementing Adaptations for Vision AutoRegressive Model
CharaConsist: Fine-Grained Consistent Character Generation
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