# SmartPhotoCrafter：自动摄影图像编辑的统一推理生成优化方法

- 来源：HuggingFace Daily Papers（社区热门论文）
- 发布时间：2026-04-21 08:00
- AIHOT 链接：https://aihot.virxact.com/items/cmo9jc3bu02uisls2j8oq9bou
- 原文链接：https://arxiv.org/abs/2604.19587

## AI 摘要

SmartPhotoCrafter是一种无需显式人工指令的自动摄影图像编辑方法，通过Image Critic模块识别图像缺陷，Photographic Artist模块执行针对性增强。该方法采用三阶段训练：基础预训练建立审美能力，推理引导的多编辑监督融入语义指导，协调式强化学习联合优化两模块。实验表明，该方法在自动摄影增强任务中优于现有生成模型，在保持照片级真实感的同时对色调指令具有更高敏感度。

## 正文

Traditional photographic image editing typically requires users to possess sufficient aesthetic understanding to provide appropriate instructions for adjusting image quality and camera parameters. However, this paradigm relies on explicit human instruction of aesthetic intent, which is often ambiguous, incomplete, or inaccessible to non-expert users. In this work, we propose SmartPhotoCrafter, an automatic photographic image editing method which formulates image editing as a tightly coupled reasoning-to-generation process. The proposed model first performs image quality comprehension and identifies deficiencies by the Image Critic module, and then the Photographic Artist module realizes targeted edits to enhance image appeal, eliminating the need for explicit human instructions. A multi-stage training pipeline is adopted: (i) Foundation pretraining to establish basic aesthetic understanding and editing capabilities, (ii) Adaptation with reasoning-guided multi-edit supervision to incorporate rich semantic guidance, and (iii) Coordinated reasoning-to generation reinforcement learning to jointly optimize reasoning and generation. During training, SmartPhotoCrafter emphasizes photo-realistic image generation, while supporting both image restoration and retouching tasks with consistent adherence to color- and tone-related semantics. We also construct a stage-specific dataset, which progressively builds reasoning and controllable generation, effective cross-module collaboration, and ultimately high-quality photographic enhancement. Experiments demonstrate that SmartPhotoCrafter outperforms existing generative models on the task of automatic photographic enhancement, achieving photo-realistic results while exhibiting higher tonal sensitivity to retouching instructions. Project page: https://github.com/vivoCameraResearch/SmartPhotoCrafter.