Abstract: A display panel and a display device are provided. The display panel includes a first substrate, a second substrate, and a liquid crystal layer between the first substrate and the second substrate. The liquid crystal layer comprises a plurality of liquid crystal molecules. When the display panel is in a first display mode, the plurality of liquid crystal molecules rotate in a slanted plane parallel to a first direction and a second direction. The first direction is slanted with respect to a thickness direction of the display panel, and the second direction is perpendicular to the thickness direction of the display panel and the first direction.

Abstract: A display device and a dimming device are provided. A dimming layer is located between a first polarizer and a second polarizer whose transmission axes are parallel to each other. When the display device is in a first display mode, long axes of the liquid crystal molecules distributed in the first polymer network are arranged along the second direction, and long axis of the liquid crystal molecules distributed in the second polymer network are arranged along the third direction. The third direction and the second direction respectively point to opposite sides of a normal line of the first polarizer.

Abstract: The disclosure relates to the field of electric vehicles, and specifically provides a target detection method, a storage medium, an electronic device, and a vehicle, to solve a problem of how to improve a processing speed, generalization, and an anti-interference capability of point cloud data to implement rapid and accurate three-dimensional target detection. For this purpose, the method of the disclosure includes: voxelizing point cloud data to be processed, and obtaining a target detection result by using a target detection network including a sparse 3D convolutional network, a two-dimensional detection network, and a detection head network in sequence. According to the method of the disclosure, point cloud data is voxelized based on voxel positions, thereby reducing dependence of the point cloud data on an absolute distance, and improving anti-interference and generalization of the network.

Abstract: The disclosure relates to the technical field of autonomous driving, and specifically provides a target detection method, a computer device, a computer-readable storage medium, and a vehicle, to solve the problem of detecting a target in a timely and accurate manner.

Abstract: The disclosure provides a drivable area detection method, a computer device, a storage medium, and a vehicle, the method of the disclosure includes: obtaining three-dimensional point clouds of a driving environment of a vehicle; estimating a ground height of the current environment based on the three-dimensional point clouds of the current environment by using a ground height estimation model based on a convolutional neural network; determining, based on the ground height, non-ground point clouds not belonging to the ground in the three-dimensional point clouds; performing obstacle detection on the non-ground point clouds to obtain one or more obstacles; and determining a drivable area in the driving environment of the vehicle based on a position of an obstacle.