ALGO: Object-Grounded Visual Commonsense Reasoning for Open-World Egocentric Action Recognition

arXiv:2406.05722v1 Announce Type: new
Abstract: Learning to infer labels in an open world, i.e., in an environment where the target "labels" are unknown, is an important characteristic for achieving autonomy. Foundation models pre-trained on enormous amounts of data have shown remarkable generalization skills through prompting, particularly in zero-shot inference. However, their performance is restricted to the correctness of the target label's search space. In an open world, this target search space can be unknown or exceptionally large, which severely restricts …

abstract action action recognition arxiv autonomy commonsense cs.cv data environment foundation however important inference labels object open-world prompting reasoning recognition skills through type visual world zero-shot