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LOCI: Spatial Linear Memory for Streaming World Models

Paper recorded by Signals 4 on 2026-09-30 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-30 on arXiv · recorded by Signals 4 on 2026-10-01

Category: cs.CV · 计算机视觉 · first seen 2026-10-01

Abstract

When a camera revisits a previously observed region, a video world model should reproduce what was there before. This requires both remembering past observations and retrieving the right one for the current viewpoint. Key-value caches preserve visual detail but grow with video length; recurrent memory is compact but compresses history into a fixed-size state, so individual past observations are no

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#21 most recent of 380 cs.CV papers we have recorded · ↑ newer: StreamRig: Exploiting Intra-Rig Geometry for Streaming Multi-Camera Od · ↓ older: Recognition of Urbanized Areas in UAV-Derived Very-High-Resolution Vis
Cite this page: LOCI: Spatial Linear Memory for Streaming World Models: the #21 most recent of 380 cs.CV papers we have recorded (as of 2026-09-30). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/loci-spatial-linear-memory-for-streaming-world-models.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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