# TUN3D: Towards Real-World Scene Understanding from Unposed Images

**Date:** 2026-01-31

M:3L co-authored TUN3D, accepted at ICRA 2026, an A*-ranked conference. It is the first system to jointly estimate room layouts and detect 3D objects in real scans from multi-view images without ground-truth camera poses or depth supervision. A lightweight sparse-convolutional backbone feeds dedicated detection and parametric wall-layout heads, enabling one model to work with point clouds, posed images, or fully unposed RGB captures and substantially advancing holistic indoor-scene understanding.

## Related link

- [Read the paper](https://arxiv.org/abs/2509.21388)

## Authoritative URLs

- [Canonical news page](https://m3l.am/news/tun3d-icra-2026)
- [All M:3L news and events](https://m3l.am/news.md)