A novel framework for domain generalizable person search that uses an automatically labeled unreal dataset for training, alleviating the need for time-consuming and labor-intensive data labeling as well as privacy issues in real datasets.
Large language models can be effectively leveraged as powerful action recognizers by projecting skeleton sequences into "action sentences" that are compatible with the models' pre-trained knowledge.