Abstract: A method for retrieving an image is provided. The method includes: extracting a global feature and a local feature of an image to be retrieved, and a global feature and a local feature of an image to be recalled by employing a preset neural network model; determining a candidate image set by matching the global feature of the image to be retrieved with the global feature of the image to be recalled and matching the local feature of the image to be retrieved with the local feature of the image to be recalled; and determining a retrieval result from the candidate image set by performing local feature verification on the image to be retrieved and a candidate image in the candidate image set. An apparatus for retrieving an image, an electronic device, and a medium are further provided.

Abstract: The present disclosure provides a method for identifying key point locations in an image. The method includes: obtaining an image to be detected, and obtaining a feature map and a saliency map of the image to be detected; generating a score response map of the image to be detected based on the feature map of the image to be detected; obtaining a first key point location of a key point on the score response map; obtaining a second key point location of the key point mapped on the image to be detected based on the first key point location; and correcting the second key point location based on the saliency map.

Abstract: The present disclosure provides a method and an apparatus for analyzing a video scenario, and relates to the field of image recognition technology. A specific embodiment includes: extracting a frame of picture from a to-be-analyzed video at a preset time interval, recording a position of each frame of picture in the video, and establishing an index table of the picture and the position; labeling the each extracted frame of picture through a pre-trained scenario classification model, and adding a label of the extracted frame of picture to the index table; aggregating labels in the index table, and marking a new label to the picture in the index table; and outputting a position corresponding to the new label in the index table.

Abstract: The present disclosure provides a method for identifying key point locations in an image. The method includes: obtaining an image to be detected, and obtaining a feature map and a saliency map of the image to be detected; generating a score response map of the image to be detected based on the feature map of the image to be detected; obtaining a first key point location of a key point on the score response map; obtaining a second key point location of the key point mapped on the image to be detected based on the first key point location; and correcting the second key point location based on the saliency map.

Abstract: A method for retrieving an image is provided. The method includes: extracting a global feature and a local feature of an image to be retrieved, and a global feature and a local feature of an image to be recalled by employing a preset neural network model; determining a candidate image set by matching the global feature of the image to be retrieved with the global feature of the image to be recalled and matching the local feature of the image to be retrieved with the local feature of the image to be recalled; and determining a retrieval result from the candidate image set by performing local feature verification on the image to be retrieved and a candidate image in the candidate image set. An apparatus for retrieving an image, an electronic device, and a medium are further provided.