Cross-Visibility-Gap Identity Persistence for 4D Scene Graphs

Jiahui Hu, Li Gao, Yu Liu, Pengzhan Zhou
10/20/2026
cs.CVcs.AI

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Abstract

4D scene graphs require persistent object identity when an object disappears inside an opaque carrier and later reappears as a fresh detection. When appearance and target-centric motion are unavailable, identity recovery must rely on relational history. We formulate cross-visibility-gap identity persistence as historical-node recovery through a remembered target--carrier binding. We introduce CVG-SGM, a perception-frontend-compatible transfer--maintain--read memory. Geometry-weighted cross-node interaction transfers target-specific evidence into carrier states, a shared per-node GRU maintains this information during transport, and a two-time readout combines stored carrier--identity compatibility with current detection--carrier geometry to recover the historical identity. In the controlled one-identity-per-carrier setting, CVG-SGM achieves 1.000 re-link accuracy, compared with 0.570 for both no-memory and parameter-count-matched no-write controls. It also generalizes to scene-disjoint, unseen longer visibility gaps. On real RGB-D/SAM2 feature-level episodes, it correctly re-links 36/36 held-out detections, compared with 28/36 for the strongest fixed carrier--identity control. Counterfactual carrier-memory swaps redirect predictions according to the swapped bindings, supporting the role of stored relational information in identity recovery. The current approach remains limited by shared-carrier identity ambiguity and does not provide end-to-end raw-video re-identification.

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Cite this paper

@article{hu2026crossvisibilitygap,
  title  = {Cross-Visibility-Gap Identity Persistence for 4D Scene Graphs},
  author = {Jiahui Hu and Li Gao and Yu Liu and Pengzhan Zhou},
  year   = {2026},
  eprint = {2610.27505},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2610.27505v1}
}

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