iSEE: Object Permanence Through Self-Supervision
Object permanence, keeping track of an object's identity and position while it is occluded, is central to video representations that track, predict and plan. Trackers that achieve it learn from boxes, track identities and visibility labels. On the other hand, self-supervised object-centric methods discover objects without labels: through slot attention, it represents a video as slots that bind to objects and follow them across frames. However, these slots are lost under occlusion, making the desired permanence impossible. Reasoning permanence is a hard problem because it requires to detect when an object becomes occluded, re-identify when object reappears, and keep the object's hidden pos...
| Authors | Pramish Paudel, Ajad Chhatkuli, Luc Van Gool et al. |
|---|---|
| Primary category | cs.CV |
| Published | 1 October 2026 |
| Last updated at source | 1 October 2026 |
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