# TransTac: Visuo-Tactile Modality Transition via Ultraviolet-Encoded Transparent Elastomers

Source: [TransTac: Visuo-Tactile Modality Transition via Ultraviolet-Encoded Transparent Elastomers](<https://www.sota2.com/research/paper/6a2106f9c10484bac23f06c5>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-06-05T05:00:04.417Z

Authors: Lingyue Yang, Bin Fang

Published: 2026-06-03T05:46:00.000Z

## Abstract

Vision-based tactile sensors (VBTS) recover high-resolution contact geometry but typically rely on opaque elastomer layers that prevent visual transparency, while RGB-D cameras provide global depth perception yet degrade significantly at close range. To address this limitation, we present TransTac, a transparent ultraviolet (UV)-encoded binocular VBTS that integrates visual observation and marker-based tactile reconstruction within a single compact device. The system employs a transparent elastomer embedded with UV-reflective markers and a prior-guided Delaunay stereo matching algorithm for robust sparse triangulation.   To reliably detect densely distributed semitransparent markers, we develop a lightweight detector that enables stable localization under contact and deformation. The proposed prior-guided Delaunay matching improves correspondence robustness by approximately 21% compared with global assignment baselines while maintaining high reconstruction accuracy. In semantic evaluation, TransTac achieves up to 83.3% zero-shot recognition accuracy on tactile images, exceeding opaque tactile baselines by approximately 50 percentage points. Embedding analysis further reveals substantially stronger cross-modal alignment with natural images, with class-center similarity increasing from around 0.2 to over 0.77. Controlled near-distance experiments quantify the degradation of RGB-D depth reliability and demonstrate extended geometric coverage enabled by visuo-tactile integration. Finally, a compact prototype is implemented with an approximate hardware cost of $70.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [Tactile Object Recognition on GelSight Mini](<https://www.sota2.com/research/sota/tactile-object-recognition-on-gelsight-mini.md>): Tactile Object Recognition; GelSight Mini; Weighted Semantic Score: not recorded.

- [Tactile Object Recognition on 9DTact](<https://www.sota2.com/research/sota/tactile-object-recognition-on-9dtact.md>): Tactile Object Recognition; 9DTact; Weighted Semantic Score: not recorded.

- [Tactile Object Recognition on TransTac](<https://www.sota2.com/research/sota/tactile-object-recognition-on-transtac.md>): Tactile Object Recognition; TransTac; Weighted Semantic Score: not recorded.

- [Tactile-Visual Embedding Alignment on GelSight Mini](<https://www.sota2.com/research/sota/tactile-visual-embedding-alignment-on-gelsight-mini.md>): Tactile-Visual Embedding Alignment; GelSight Mini; Accuracy: not recorded.

- [Tactile-Visual Embedding Alignment on 9DTact](<https://www.sota2.com/research/sota/tactile-visual-embedding-alignment-on-9dtact.md>): Tactile-Visual Embedding Alignment; 9DTact; Accuracy: not recorded.

- [Tactile-Visual Embedding Alignment on TransTac](<https://www.sota2.com/research/sota/tactile-visual-embedding-alignment-on-transtac.md>): Tactile-Visual Embedding Alignment; TransTac; Accuracy: not recorded.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2606.04477>)

[PDF](<https://arxiv.org/pdf/2606.04477.pdf>)