MemoVis: A GenAI-Powered Tool for Creating Companion Reference Images for 3D Design Feedback
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Abstract (arXiv)
Providing asynchronous feedback is a critical step in the 3D design workflow. A common approach to providing feedback is to pair textual comments with companion reference images, which helps illustrate the gist of text. Ideally, feedback providers should possess 3D and image editing skills to create reference images that can effectively describe what they have in mind. However, they often lack such skills, so they have to resort to sketches or online images which might not match well with the current 3D design. To address this, we introduce MemoVis, a text editor interface that assists feedback providers in creating reference images with generative AI driven by the feedback comments. First, a novel real-time viewpoint suggestion feature, based on a vision-language foundation model, helps feedback providers anchor a comment with a camera viewpoint. Second, given a camera viewpoint, we introduce three types of image modifiers, based on pre-trained 2D generative models, to turn a text comment into an updated version of the 3D scene from that viewpoint. We conducted a within-subjects study with feedback providers, demonstrating the effectiveness of MemoVis. The quality and explicitness of the companion images were evaluated by another eight participants with prior 3D design experience.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Sep 2024.
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Citing papers per year: 2024: 1; 2025: 5; 2026: 1.
7 papers.
- 2025DesignWeaver: Dimensional Scaffolding for Text-to-Image Product Designcited by 6
- 2025GenTune: Toward Traceable Prompts to Improve Controllability of Image Refinement in Environment Designcited by 5
- 2024Image First or Text First? Optimising the Sequencing of Modalities in Large Language Model Prompting and Reasoning Taskscited by 2
- 2025AnimAgents: Coordinating Multi-Stage Animation Pre-Production with Human-Multi-Agent Collaborationcited by 1
- 2025SweeperBot: Making 3D Browsing Accessible through View Analysis and Visual Question Answeringcited by 0
- 2025GRAPHIC--Guidelines for Reviewing Algorithmic Practices in Human-centred Design and Interaction for Creativitycited by 0
- 2026MOONWALK: Mediating Operations with Intent-Evidence-Action Alignment Across Junior-Supervisor Review Workflows in Animation/VFX Pre-Productioncited by 0
- 2026MOONWALK: Mediating Operations with Intent-Evidence-Action Alignment Across Junior-Supervisor Review Workflows in Animation/VFX Pre-Production9 Sep 2026
- 2025AnimAgents: Coordinating Multi-Stage Animation Pre-Production with Human-Multi-Agent Collaboration22 Nov 2025
- 2025GRAPHIC--Guidelines for Reviewing Algorithmic Practices in Human-centred Design and Interaction for Creativity21 Nov 2025
- 2025SweeperBot: Making 3D Browsing Accessible through View Analysis and Visual Question Answering18 Nov 2025
- 2025GenTune: Toward Traceable Prompts to Improve Controllability of Image Refinement in Environment Design21 Aug 2025
- 2025DesignWeaver: Dimensional Scaffolding for Text-to-Image Product Design14 Feb 2025
- 2024Image First or Text First? Optimising the Sequencing of Modalities in Large Language Model Prompting and Reasoning Tasks4 Oct 2024
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- 2024Sketch2NeRF: Multi-view Sketch-guided Text-to-3D Generation
- 2024Idea23D: Collaborative LMM Agents Enable 3D Model Generation from Interleaved Multimodal Inputs
- 2024SketchDream: Sketch-based Text-to-3D Generation and Editing
- 2025Sel3DCraft: Interactive Visual Prompts for User-Friendly Text-to-3D Generation
- 2024Visual Prompting with Iterative Refinement for Design Critique Generation
- 2026Co-generation of Layout and Shape from Text via Autoregressive 3D Diffusion
- 2023Control3D: Towards Controllable Text-to-3D Generation
- 2024MUSES: 3D-Controllable Image Generation via Multi-Modal Agent Collaboration