Editing images via instruction provides a natural way to generate interactive content, but it is a big challenge due to the higher requirement of scene understanding and generation. Prior work utilizes a chain of large language models, object segmentation models, and editing models for this task. However, the understanding models provide only a single modality ability, restricting the editing quality. We aim to bridge understanding and generation via a new multi-modality model that provides the intelligent abilities to instruction-based image editing models for more complex cases. To achieve this goal, we individually separate the instruction editing task with the multi-modality chain of thought prompts, i.e., Chain-of-Thought (CoT) planning, editing region reasoning, and editing. For Chain-of-Thought planning, the large language model could reason the appropriate sub-prompts considering the instruction provided and the ability of the editing network. For editing region reasoning, we train an instruction-based editing region generation network with a multi-modal large language model. Finally, a hint-guided instruction-based editing network is proposed for editing image generations based on the sizeable text-to-image diffusion model to accept the hints for generation. Extensive experiments demonstrate that our method has competitive editing abilities on complex real-world images.
FreeEdit: Mask-free Reference-based Image Editing with Multi-modal Instruction
Chinese Academy of Sciences Institute of Information Engineering（中国科学院信息工程研究所）；Institute of Artificial Intelligence, Beihang University（北京航空航天大学人工智能研究院）；Meituan（美团）
East China Normal University（华东师范大学）；Xiaohongshu Inc.（小红书）；KLATASDS, MOE, China（中国教育部统计与数据科学重点实验室）；The Chinese University of Hong Kong（香港中文大学）；Zhejiang University（浙江大学）；Fudan University（复旦大学）；University of Oxford（牛津大学）；Shanghai Jiao Tong University（上海交通大学）；University of Science and Technology of China（中国科学技术大学）；Nanjing University（南京大学）
Tuning-free Instruction-based Video Editing Via Structural Noise Initialization and Guidance
JIUTIAN Research, China Mobile（中国移动极天研究院）；School of Intelligence Science and Technology, Nanjing University（南京大学智能科学与技术学院）；State Key Laboratory of Novel Software Technology, Nanjing University（南京大学新型软件技术国家重点实验室）
Beyond Editing Pairs: Fine-Grained Instructional Image Editing via Multi-Scale Learnable Regions
Department of Electronic Engineering and Computer Science University of California, Irvine（电子工程与计算机科学系 加州大学尔湾分校）；Department of Computer Science University of Alabama at Birmingham（计算机科学系 阿拉巴马大学伯明翰分校）
EditCaption: Human-Refined SFT and HAE-DPO for Image Editing Instruction Synthesis
Peking University（北京大学）；The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳））；Tsinghua University（清华大学）；Beihang University（北京航空航天大学）；Xiaohongshu Inc.（小红书公司）
University of Sydney（悉尼大学）；Microsoft Research（微软研究院）；Fudan University（复旦大学）；Nankai University（南开大学）；Shanghai Jiao Tong University（上海交通大学）；Tsinghua University（清华大学）；University of Science and Technology of China（中国科学技术大学）；University of Waterloo（滑铁卢大学）
We propose a method for editing images from human instructions: given an input image and a written instruction that tells the model what to do, our model follows these instructions to edit the image. To obtain training data for this problem, we combine the knowledge of two large pretrained models -- a language model (GPT-3) and a text-to-image model (Stable Diffusion) -- to generate a large dataset of image editing examples. Our conditional diffusion model, InstructPix2Pix, is trained on our generated data, and generalizes to real images and user-written instructions at inference time. Since i…
JAVEDIT: Joint Audio-Visual Instruction-Guided Video Editing with Agentic Data Curation
Zhejiang University（浙江大学）；Tencent Youtu Lab（腾讯优图实验室）；Nanjing University（南京大学）；University of Auckland（奥克兰大学）；Fudan University（复旦大学）；National University of Singapore（新加坡国立大学）
MIGE: Mutually Enhanced Multimodal Instruction-Based Image Generation and Editing
State Key Laboratory of AI Safety, Institute of Computing Technology, Chinese Academy of Sciences（人工智能安全国家重点实验室，计算技术研究所，中国科学院）；University of Chinese Academy of Sciences（中国科学院大学）
SmartEdit: Exploring Complex Instruction-based Image Editing with Multimodal Large Language Models
University of Macau（澳门大学）；ARC Lab, Tencent PCG（腾讯平台与内容事业群ARC实验室）；Tencent AI Lab（腾讯人工智能实验室）；Shenzhen Institute of Advanced Technology（深圳先进技术研究院）；Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）；The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳））；Shenzhen Research Institute of Big Data（深圳大数据研究院）；Tsinghua University（清华大学）
IVEBench: Modern Benchmark Suite for Instruction-Guided Video Editing Assessment
Zhejiang University（浙江大学）；Tencent Youtu Lab（腾讯优图实验室）；Shanghai Jiao Tong University（上海交通大学）；University of Auckland（奥克兰大学）；National University of Singapore（新加坡国立大学）
