Abstract: The present application relates to the technical field of deep learning and pose estimation, and more particularly, to a contextual instance decoupling (CID)-based multi-person pose estimation (MPPE) method and apparatus. The method includes: acquiring a preset number of images containing multiple persons; inputting the images containing multiple persons, as a training sample, into a CID-based MPPE model for training; and performing pose estimation on a target image using the trained CID-based MPPE model, the CID-based MPPE model being provided with an instance information abstraction module, a global feature decoupling module and a heatmap estimation module. The method and apparatus of the present application can explore context clues over a greater range, thus being robust to spatial detection errors and superior in both accuracy and efficiency.

Abstract: The present application discloses a method and a system for person re-identification, the method including: inputting a training set to a model-to-be-trained, and determining a single-class label and memory features of each image data in the training set; determining multi-class labels through positive label prediction according to the single-class labels and a memory feature set; determining classification scores according to image features of each image data in the training set and the memory feature set; determining a multi-label classification loss according to the multi-class labels and the classification scores; and updating and training the model-to-be-trained to obtain a re-identification model according to the multi-label classification loss.

Abstract: The present application discloses a method and a system for person re-identification, the method including: inputting a training set to a model-to-be-trained, and determining a single-class label and memory features of each image data in the training set; determining multi-class labels through positive label prediction according to the single-class labels and a memory feature set; determining classification scores according to image features of each image data in the training set and the memory feature set; determining a multi-label classification loss according to the multi-class labels and the classification scores; and updating and training the model-to-be-trained to obtain a re-identification model according to the multi-label classification loss.

Abstract: The invention provides compounds of formula (I) having (?) or (+) configuration, or pharmaceutically acceptable salts thereof, wherein R1 is H or halo; R2 is CF3, CN, or halo; R3 is linear or branched alkyl having 1 to 6 carbon atoms, or cycloalkyl having 3 to 6 carbon atoms. The invention also relates to methods for preparing the said compounds and the composition comprising the same. The compounds of the present invention have the effect of ?2-receptor agonist and can be used for the treatment of asthma or bronchitis.