MAOAM: Unified Object and Material Selection with Vision-Language Models
Jaden Park, Valentin Deschaintre, Jason Kuen, Kangning Liu, Iliyan Georgiev, Krishna Kumar Singh, Yong Jae Lee, Michael Fischer
Abstract
Selection is a core operation in interactive image editing, enabling tasks such as composition or manipulation. To be practically useful, a user should be able to specify and disambiguate the desired selection region through either text- or click-based interactions, and the system should support selecting not only objects but also other criteria, such as materials. Material-based selection can be particularly valuable for tasks like re-texturing surfaces or consistently editing all instances of a specific material in a scene. However, existing vision–language-model (VLM) based selection methods are largely object-centric and typically support only a single interaction modality, limiting their applicability in real editing workflows.
Ask about this paper
Ask your agent about it.
Lune has read the top-tier papers around this one, so every answer names the papers it rests on.
Related papers
- Materialistic: Selecting Similar Materials in ImagesPrafull Sharma, Julien Philip, Michaël Gharbi, Bill Freeman et al.SIGGRAPH 2023 · 23 citations
- PBR3DGen: A VLM-Guided Mesh Generation with High-Quality PBR TextureXiaokang Wei, Bowen Zhang, Xianghui Yang, Yuxuan Wang et al.AAAI 2026 · 1 citation
- Alterbute: Editing Intrinsic Attributes of Objects in ImagesTal Reiss, Daniel Winter, Matan Cohen, Alex Rav-Acha et al.ICML 2026
- Unifying Automatic and Interactive Matting with Pretrained ViTsZixuan Ye, Wenze Liu, He Guo, Yujia Liang et al.CVPR 2024 · 7 citations
- SINE: Semantic-driven Image-based NeRF Editing with Prior-guided Editing FieldChong Bao, Yinda Zhang, Bangbang Yang, Tianxing Fan et al.CVPR 2023
