Place-Recognition

To perform long-horizon tasks, agents need memory that supports reasoning over time and reduces the search space. In robotics there is substantial work on spatial and episodic memory, most of which combines geometry, pose, and tracking. This post asks a simpler question: How far can a pure appearance-based approach using a modern vision-language embedding (SigLIP2) go for place recognition and basic memory under real object and viewpoint change? Overview I test a lightweight online appearance-based visual memory. Each image is embedded with SigLIP2 and either assigned to an existing place cluster or used to start a new one, based on cosine similarity. For a known place, previous observations can be retrieved. High-level change descriptions are generated with a vision-language model only as a secondary step. ...