Recent advances in generative AI allow users to create 3D models from text or images. However, these models prioritize visual plausibility over geometric accuracy, often generating results with flaws that compromise their intended use post-fabrication. We present InstructMesh, an interactive post-generation refinement tool that enables selective repair of generative 3D models through region selection and targeted operations, such as opening or sealing voids, or adjusting local thickness. Users can invoke edit operations via natural language prompts or slider controls. By operating directly on the intermediate latent representation, InstructMesh allows users to apply robust geometric corrections without requiring expert modeling skills. To inform our design, we first analyze common fabrication-related failure modes in outputs from state-of-the-art generative tools. We then conduct two user studies, demonstrating that novices can identify and perform fabrication-relevant repairs on generative outputs using InstructMesh, and revealing user preference for hybrid interfaces that combine slider controls with natural language input.
Generative AI lets anyone create rich visual content in seconds, yet translating that content into a physically fabricable artifact still demands manual decomposition, occlusion repair, and structural verification that most tools leave entirely to the user. We present FabDreamer, an image-to-physical system that carrie...
Chen-Feng Gao, Zeya Chen, An Yang et al.· 0 citations
Current 3D generation methods lack explicit local control: geometric adherence is often defined by a global control strength, and appearance cannot be specified locally. We present SpaceFlow, a training-free pipeline for locally controllable 3D generation from text descriptions and a collection of geometric primitives....
Neil De La Fuente, Joan Lafuente, Mukhammadali Sayfiddinov et al.· 0 citations
The proposed framework leverages the reasoning and language-understanding capabilities of large language models (LLMs), while grounding the reasoning with geometry evidence and structured material/printer knowledge to generate reliable pre-print recommendations.
Zhao-Da Du, Qiaojie Zheng, Xiaoli Zhang· 0 citations
Consumer-grade Fused Deposition Modeling (FDM) 3D printing has become increasingly commonplace, but novice users often lack the expertise to harness the power of their hardware. Among other issues, users tend to over-rely on standard materials (e.g., PLA), despite modern consumer printers being capable of processing a...
Naim Hadzic, Ulrich von Zadow· Message Understanding Confer...· 0 citations
This work presents a training-free multi-agent system that edits existing 3D meshes directly in Blender by emulating the iterative workflow of human artists, and views this work as an exploratory step toward visual-centric agentic geometry editing in professional graphics software.
Bo Pang, Jiaqi Pan, Xiao-Chen Zhang et al.· 0 citations
Part-level control is essential for modern 3D asset creation, where objects are frequently edited, reused, animated, or fabricated through their individual components. In many such workflows, users need only several specific components rather than a complete object decomposition. However, existing 3D generation methods...
Jia-Hao Chang, Dong Du, Wan-Hu Sun et al.· 0 citations
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