Abstract: Embodiments of the application provide a method, apparatus, server, and terminal device for obtaining a vehicle loss assessment image. A computer-implemented method for obtaining a vehicle loss assessment image comprises: receiving video data of a damaged vehicle; detecting one or more video images in the video data to identify a damaged portion in the one or more video images; classifying the one or more video images into one or more candidate image classification sets of the damaged portion based on the identified damaged portion; and selecting a vehicle loss assessment image from the one or more candidate image classification sets according to a screening condition.

Abstract: Methods, systems, and computer-readable storage media for generation of a vehicle repair plan. Implementations include actions of receiving vehicle damage data including an image of a damaged vehicle. The vehicle damage data is processed to determine a component region. The component region is processed to determine a damaged area and a damage type of a portion of the damaged vehicle. A maintenance plan is generated for the damaged vehicle based on the damaged area and the damage type. The maintenance plan is initiated for the damaged vehicle.

Abstract: A vehicle insurance image processing method includes: acquiring a vehicle insurance image; processing the vehicle insurance image by using a preset image classification algorithm, to determine at least one category label of the vehicle insurance image; and storing, based on classification, the vehicle insurance image in a corresponding usage scenario according to the at least one category label.

Abstract: Methods, systems, and computer-readable storage media for generation of a vehicle repair plan. Implementations include actions of receiving vehicle damage data including an image of a damaged vehicle. The vehicle damage data is processed to determine a damaged area and a damage type of a portion of the damaged vehicle. A repair plan is generated for the damaged vehicle based on the damaged area and the damage type. The repair plan is initiated for the damaged vehicle.

Abstract: Methods, systems, and computer-readable storage media for generation of a vehicle repair plan. Implementations include actions of receiving vehicle damage data including an image of a damaged vehicle. The vehicle damage data is processed to determine a component region. The component region is processed to determine a damaged area and a damage type of a portion of the damaged vehicle. A maintenance plan is generated for the damaged vehicle based on the damaged area and the damage type. The maintenance plan is initiated for the damaged vehicle.

Abstract: A vehicle insurance image processing method includes: acquiring a vehicle insurance image; processing the vehicle insurance image by using a preset image classification algorithm, to determine at least one category label of the vehicle insurance image; and storing, based on classification, the vehicle insurance image in a corresponding usage scenario according to the at least one category label.

Abstract: Embodiments of the specification provide a method, apparatus, server and terminal device for obtaining a vehicle loss assessment image. The method may include: receiving video data of a damaged vehicle and information of a damaged portion of the damaged vehicle; extracting one or more video images from the video data; classifying the one or more video images into one or more candidate image classification sets of the damaged portion based on the information of the damaged portion; and selecting a vehicle loss assessment image from the one or more candidate image classification sets according to a screening condition.

Abstract: Embodiments of the application provide a method, apparatus, server, and terminal device for obtaining a vehicle loss assessment image. A computer-implemented method for obtaining a vehicle loss assessment image comprises: receiving video data of a damaged vehicle; detecting one or more video images in the video data to identify a damaged portion in the one or more video images; classifying the one or more video images into one or more candidate image classification sets of the damaged portion based on the identified damaged portion; and selecting a vehicle loss assessment image from the one or more candidate image classification sets according to a screening condition.

Abstract: Methods, systems, and computer-readable storage media for generation of a vehicle repair plan. Implementations include actions of receiving vehicle damage data including an image of a damaged vehicle. The vehicle damage data is processed to determine a first vehicle component. The first image is matched to a second image to determine a second vehicle component within the second image. The second vehicle component is processed to determine a damaged area and a damage type of a portion of the damaged vehicle. A maintenance plan is generated for the damaged vehicle based on the damaged area and the damage type. The maintenance plan is initiated for the damaged vehicle.

Abstract: Methods, systems, and computer-readable storage media for generation of a vehicle repair plan. Implementations include actions of receiving vehicle damage data including an image of a damaged vehicle. The vehicle damage data is processed to determine a damaged area and a damage type of a portion of the damaged vehicle. A repair plan is generated for the damaged vehicle based on the damaged area and the damage type. The repair plan is initiated for the damaged vehicle.

Abstract: Methods, systems, and computer-readable storage media for generation of a vehicle repair plan. Implementations include actions of receiving vehicle damage data including an image of a damaged vehicle. The vehicle damage data is processed to determine a component region. The component region is processed to determine a damaged area and a damage type of a portion of the damaged vehicle. A maintenance plan is generated for the damaged vehicle based on the damaged area and the damage type. The maintenance plan is initiated for the damaged vehicle.

Abstract: Methods, systems, and computer-readable storage media for generation of a vehicle repair plan. Implementations include actions of receiving vehicle damage data including an image of a damaged vehicle. The vehicle damage data is processed to determine a component region. The component region is processed to determine a damaged area and a damage type of a portion of the damaged vehicle. A maintenance plan is generated for the damaged vehicle based on the damaged area and the damage type. The maintenance plan is initiated for the damaged vehicle.

Abstract: Methods, systems, and computer-readable storage media for generation of a vehicle repair plan. Implementations include actions of receiving vehicle damage data including an image of a damaged vehicle. The vehicle damage data is processed to determine a first vehicle component. The first image is matched to a second image to determine a second vehicle component within the second image. The second vehicle component is processed to determine a damaged area and a damage type of a portion of the damaged vehicle. A maintenance plan is generated for the damaged vehicle based on the damaged area and the damage type. The maintenance plan is initiated for the damaged vehicle.

Abstract: Methods, systems, and computer-readable storage media for generation of a vehicle repair plan. Implementations include actions of receiving vehicle damage data including an image of a damaged vehicle. The vehicle damage data is processed to determine a damaged area and a damage type of a portion of the damaged vehicle. A repair plan is generated for the damaged vehicle based on the damaged area and the damage type. The repair plan is initiated for the damaged vehicle.

Abstract: Techniques are described to generate an index for a texture. The index can be used to retrieve a portion of one or more textures from a cache. The index can be adapted based on static texture attributes or direction attributes in order to attempt to achieve texture cache efficiency. Static texture attributes can include, bit are not limited to, 1-dimensional texture, 2-dimensional texture, 3-dimensional texture, or MIPmaps texture, original memory address. Direction attributes can be, but are not limited to, u-major or v-major directions.

Abstract: Techniques are described to generate an index for a texture. The index can be used to retrieve a portion of one or more textures from a cache. The index can be adapted based on static texture attributes or direction attributes in order to attempt to achieve texture cache efficiency. Static texture attributes can include, bit are not limited to, 1-dimensional texture, 2-dimensional texture, 3-dimensional texture, or MIPmaps texture, original memory address. Direction attributes can be, but are not limited to, u-major or v-major directions.