Reverse engineering 3D computer-aided design (CAD) models from images is an important task for many downstream applications including interactive editing, manufacturing, architecture, robotics, etc. The difficulty of the task lies in vast representational disparities between the CAD output and the image input. CAD models are precise, programmatic constructs that involve sequential operations combining discrete command structure with continuous attributes, making it challenging to learn and optimize in an end-to-end fashion. Concurrently, input images introduce inherent challenges such as photometric variability and sensor noise, complicating the reverse engineering process. In this work, we introduce a novel approach that conditionally factorizes the task into two sub-problems. First, we leverage vision-language foundation models (VLMs), a finetuned Llama3.2, to predict the global discrete base structure with semantic information. Second, we propose TrAssembler that, conditioned on the discrete structure with semantics, predicts the continuous attribute values. To support the training of our TrAssembler, we further constructed an annotated CAD dataset of common objects from ShapeNet. Putting all together, our approach and data demonstrate significant first steps towards CAD-ifying images in the wild. Code and data can be found in https://github.com/qq456cvb/Img2CAD.
Lung-CADex: Fully automatic Zero-Shot Detection and Classification of Lung Nodules in Thoracic CT Images
Faculty of Electronics and Electrical Engineering, University of Engineering and Technology, Taxila（塔克西拉工程技术大学电子与电气工程学院）；Center for Research in Computer Vision, University of Central Florida（中佛罗里达大学计算机视觉研究中心）；Sheikh Zayed Institute for Pediatric Surgical Innovation, Childrens National Hospital（儿童国家医院谢赫扎耶德儿科外科创新研究所）；School of Medicine and Health Sciences, George Washington University（乔治华盛顿大学医学与健康科学学院）
OpenECAD: An Efficient Visual Language Model for Editable 3D-CAD Design
Software Engineering Institute, East China Normal University（华东师范大学软件工程研究所）；National Trusted Embedded Software Engineering Technology Research Center, Shanghai, China（国家可信嵌入式软件工程技术研究中心）
Seek-CAD: A Self-refined Generative Modeling for 3D Parametric CAD Using Local Inference via DeepSeek
College of Computer Science and Artificial Intelligence, Fudan University（计算机科学与人工智能学院，复旦大学）；School of Information and Intelligent Science, Donghua University（信息与智能科学学院，东华大学）
MV-GEL: Language-Driven Multi-View Geometric Entity Localization on Meshes
Helmholtz Zentrum Hereon（亥姆霍兹赫里恩研究中心）；Institute for Continuum and Material Mechanics, Hamburg University of Technology（汉堡工业大学连续介质与材料力学研究所）；German Research Center for Artificial Intelligence（德国人工智能研究中心）
Diffusion-based Cumulative Adversarial Purification for Vision Language Models
KTH Royal Institute of Technology（皇家理工学院）；Swiss Federal Institute of Technology Lausanne（洛桑联邦理工学院）；University of California, Los Angeles（加州大学洛杉矶分校）；Karlsruhe Institute of Technology（卡尔斯鲁厄理工学院）；CISPA Helmholtz Center for Information Security（信息安全赫尔姆霍兹中心）；RISE Research Institutes of Sweden（瑞典RISE研究机构）；Halmstad University（哈马碧大学）
Medical Context Distorts Decisions in Clinical Vision Language Models
MICS（医学信息学中心）；CentraleSupélec - Université Paris-Saclay（中央超导学院 - 巴黎萨克雷大学）；Cancer Data Science Unit（癌症数据科学单元）；IHU PRISM；National Institute in Precision Oncology（精准肿瘤学国家研究所）；University Paris-Saclay（巴黎萨克雷大学）；CentraleSupelec（中央超导学院）；Gustave Roussy（儒勒-维维安-圣拉扎尔医院）；INSERM（国家医学研究院）；CONICET（阿根廷国家科研与技术创新委员会）；Universidad de Buenos Aires（布宜诺斯艾利斯大学）
BRep Boundary and Junction Detection for CAD Reverse Engineering
German Research Center for Artificial Intelligence (DFKI GmbH)（德国人工智能研究中心（DFKI GmbH））；RPTU Kaiserslautern-Landau（凯泽斯劳滕-兰道工业大学（RPTU Kaiserslautern-Landau））
OS-Genesis: Automating GUI Agent Trajectory Construction via Reverse Task Synthesis
Shanghai AI Laboratory（上海人工智能实验室）；The University of Hong Kong（香港大学）；Johns Hopkins University（约翰霍普金斯大学）；Shanghai Jiao Tong University（上海交通大学）；University of Oxford（牛津大学）；Hong Kong University of Science and Technology（香港科技大学）
A Semi-Supervised Framework for Breast Ultrasound Segmentation with Training-Free Pseudo-Label Generation and Label Refinement
Tohoku University Graduate School of Medicine（东北大学医学研究科）；Advanced Institute of Convergence Knowledge Informatics（融合知识信息先进研究所）；Research Institute of Electrical Communication, Tohoku University（东北大学电气通信研究所）；National Institute of Technology, Sendai College（名古屋国立技术大学送崎学院）；State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center（南方肿瘤学国家重点实验室，中山大学肿瘤中心）；Department of Mathematics, Informatics, and Cybernetics, University of Chemistry and Technology（化学与技术大学数学、信息学与自动控制系）；School of Software Technology, Zhejiang University（浙江大学软件技术学院）；Southeast University, School of Cyber Science and Engineering（东南大学网络科学与工程学院）
CADCrafter: Generating Computer-Aided Design Models from Unconstrained Images
Nanyang Technological University（南洋理工大学）；Institute for Infocomm Research, A*STAR（新加坡科技研究局信息通信研究院）；KOKONI3D；Moxin (Huzhou) Technology Co., LTD.（墨芯（湖州）科技有限公司）；The University of Texas at Austin（德克萨斯大学奥斯汀分校）；Westlake University（西湖大学）；Centre for Frontier AI Research, A*STAR（新加坡科技研究局前沿人工智能研究院）；Zhejiang University（浙江大学）
