GaMi: Geometry-Agnostic Material Identification via Cross-Modal Subtractive Disentanglement
Non-contact material identification enables adaptive interaction for embodied intelligence yet faces challenges from geometry-induced variations (e.g., orientation, shape, distance) and single-modality ambiguities. In this paper, we present GaMi, a multimodal material identification system integrating mmWave and acoustic sensing to robustly operate under unconstrained geometric conditions. By leveraging the insight of shared geometric consistency between co-located bimodal sensors, GaMi employs an intra-sample cross-modal subtractive disentanglement framework. By semantically aligning modalities and subtracting the shared geometric context, it isolates intrinsic material features. Further...
| Authors | Zhiwei Chen, Yijie Li, Yimo Zhang et al. |
|---|---|
| Primary category | cs.ET |
| Published | 29 May 2026 |
| Last updated at source | 29 May 2026 |
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