Generating style-consistent images is a common task in the e-commerce field, and current methods are largely based on diffusion models, which have achieved excellent results. This paper introduces the concept of the QKV (query/key/value) level, referring to modifications in the attention maps (self-attention and cross-attention) when integrating UNet with image conditions. Without disrupting the product's main composition in e-commerce images, we aim to use a train-free method guided by pre-set conditions. This involves using shared KV to enhance similarity in cross-attention and generating mask guidance from the attention map to cleverly direct the generation of style-consistent images. Our method has shown promising results in practical applications.
MAGIC: Few-Shot Mask-Guided Anomaly Inpainting with Prompt Perturbation, Spatially Adaptive Guidance, and Context Awareness
Department of AI Semiconductor Engineering, Hanyang University, Seoul, Korea（汉阳大学人工智能半导体工程系）；Department of Electronic Engineering, Hanyang University, Seoul, Korea（汉阳大学电子工程系）
LAND: Lung and Nodule Diffusion for 3D Chest CT Synthesis with Anatomical Guidance
Eurecat, Centre Tecnològic de Catalunya（埃鲁卡特技术中心，加泰罗尼亚技术中心）；Dept. de Matemàtiques i Informàtica, Universitat de Barcelona（巴塞罗那大学数学与计算机系）；Barcelona Supercomputing Center (BSC)（巴塞罗那超级计算中心）
MedDiff-FT: Data-Efficient Diffusion Model Fine-tuning with Structural Guidance for Controllable Medical Image Synthesis
Guangdong Provincial Key Laboratory of Ultra High Definition Immersive Media Technology, Peking University Shenzhen Graduate School South China University of Technology, China
Unbiased Multi-Modality Guidance for Image Inpainting
Institute of Software Chinese Academy of Sciences（中国科学院软件研究所）；University of Chinese Academy of Sciences（中国科学院大学）；Kitware（Kitware公司）；Nanjing Institute of Software Technology（南京软件技术研究院）
ModaFlow: Modality-Aware Flow Matching for High-Fidelity Virtual Try-On
South China University of Technology（华南理工大学）；Universitat de Barcelona（巴塞罗那大学）；Computer Vision Center（计算机视觉中心）；Guangdong Provincial Key Laboratory of Multimodal Big Data Intelligent Analysis（广东省多模态大数据智能分析重点实验室）
Fundus2Video: Cross-Modal Angiography Video Generation from Static Fundus Photography with Clinical Knowledge Guidance
The Hong Kong Polytechnic University（香港理工大学）；Clemson University（克莱姆森大学）；École Polytechnique Fédérale de Lausanne (EPFL)（洛桑联邦理工学院）；Monash University（莫纳什大学）；Sun Yat-sen University（中山大学）
Image AID via continuous-time reinforcement learning
Department of Industrial Engineering and Operations Research, Columbia University, New York, NY 10027, USA（工业工程与运筹学系，哥伦比亚大学，纽约，NY 10027，美国）；Department of Industrial Engineering and Operations Research & Data Science Institute, Columbia University, New York, NY 10027, USA（工业工程与运筹学系及数据科学研究所，哥伦比亚大学，纽约，NY 10027，美国）
SP-Guard: Selective Prompt-adaptive Guidance for Safe Text-to-Image Generation
Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea（电气与计算机工程系，首尔国立大学，首尔，韩国）；IPAI / ASRI / INMC, Seoul National University, Seoul, South Korea（IPAI/ASRI/INMC，首尔国立大学，首尔，韩国）
When Test-Time Guidance Is Enough: Fast Image and Video Editing with Diffusion Guidance
CMAP, Ecole Polytechnique（巴黎综合理工学院CMAP实验室）；Institute of Foundation Models（基础模型研究所）；MBZUAI（穆罕默德·本·扎耶德人工智能大学）；EPITA（法国高等信息技术学院）；Sorbonne University（索邦大学）；Lagrange Mathematics and Computing Research Center（拉格朗日数学与计算研究中心）；EPITA Research Lab（EPITA研究实验室）；KTH Royal Institute of Technology（瑞典皇家理工学院）
CMAMRNet: A Contextual Mask-Aware Network Enhancing Mural Restoration Through Comprehensive Mask Guidance
University of Macau（澳门大学）；Guangdong University of Technology（广东工业大学）；University of Chinese Academy of Sciences（中国科学院大学）；Shanghai Jiao Tong University（上海交通大学）；Shenzhen Polytechnic University（深圳职业技术大学）
SARD: Segmentation-Aware Anomaly Synthesis via Region-Constrained Diffusion with Discriminative Mask Guidance
Global Institute of Future Technology（未来技术全球研究所）；Shanghai Jiao Tong University（上海交通大学）；Department of Intelligent Manufacturing（智能制造系）；Contemporary Amperex Technology Co.,Ltd（当代电子技术有限公司）
Product Image Recognition with Guidance Learning and Noisy Supervision
Southwest Jiaotong University（西南交通大学）；Shenzhen Institutes of Advanced Technology, CAS（中国科学院深圳先进技术研究院）；University of Massachusetts at Amherst（马萨诸塞大学阿默斯特分校）；Vipshop Inc.（唯品会公司）
FlowSeg: Dynamic Semantic Guidance for LLM-Conditioned Segmentation
School of Computer Science, Beijing Institute of Technology（北京理工大学计算机科学学院）；School of Computer Science, University of Birmingham（伯明翰大学计算机科学学院）；WEI Lab, Institute of Information Science, Beijing Jiaotong University（北京交通大学信息科学学院WEI实验室）；Beijing Key Laboratory of Advanced Information Science（北京高级信息科学重点实验室）
