Computer implemented method for object detection, the method comprising the following steps carried out by computer hardware components: - determining a grid, the grid comprising a plurality of grid cells; - determining, for a plurality of time steps, for each grid cell, a plurality of respective radar detection data, each radar detection data indicating a plurality of radar properties; - determining, for each time step, a respective radar map indicating a pre-determined radar map property in each grid cell; - converting the respective radar detection data of the plurality of grid cells for the plurality of time steps to a point representation of pre-determined first dimensions; - converting the radar maps for the plurality of time steps to a map representation of pre-determined second dimensions, wherein the pre-determined first dimensions and the pre-determined second dimensions are at least partially identical; - concatenating the point representation and the map representation to obtain concatenated data; and - carrying out object detection based on the concatenated data; wherein the grid comprises a pre-determined height and a pre-determined width; wherein the point representation comprises a four-dimensional point tensor, wherein a first dimension of the point tensor corresponds to the number of the plurality of time steps, a second dimension of the point tensor corresponds to the height of the grid, and a third dimension of the point tensor corresponds to the width of the grid; and wherein the map representation comprises a four-dimensional map tensor, wherein a first dimension of the map tensor corresponds to the number of the plurality of time steps, a second dimension of the map tensor corresponds to the height of the grid, and a third dimension of the map tensor corresponds to the width of the grid. the method comprising the following steps carried out by computer hardware components: - determining a grid, the grid comprising a plurality of grid cells; - determining, for a plurality of time steps, for each grid cell, a plurality of respective radar detection data, each radar detection data indicating a plurality of radar properties; - determining, for each time step, a respective radar map indicating a pre-determined radar map property in each grid cell; - converting the respective radar detection data of the plurality of grid cells for the plurality of time steps to a point representation of pre-determined first dimensions; - converting the radar maps for the plurality of time steps to a map representation of pre-determined second dimensions, wherein the pre-determined first dimensions and the pre-determined second dimensions are at least partially identical; - concatenating the point representation and the map representation to obtain concatenated data; and - carrying out object detection based on the concatenated data; - determining a grid, the grid comprising a plurality of grid cells; - determining, for a plurality of time steps, for each grid cell, a plurality of respective radar detection data, each radar detection data indicating a plurality of radar properties; - determining, for each time step, a respective radar map indicating a pre-determined radar map property in each grid cell; - converting the respective radar detection data of the plurality of grid cells for the plurality of time steps to a point representation of pre-determined first dimensions; - converting the radar maps for the plurality of time steps to a map representation of pre-determined second dimensions, wherein the pre-determined first dimensions and the pre-determined second dimensions are at least partially identical; - concatenating the point representation and the map representation to obtain concatenated data; and - carrying out object detection based on the concatenated data; wherein the grid comprises a pre-determined height and a pre-determined width; wherein the point representation comprises a four-dimensional point tensor, wherein a first dimension of the point tensor corresponds to the number of the plurality of time steps, a second dimension of the point tensor corresponds to the height of the grid, and a third dimension of the point tensor corresponds to the width of the grid; and wherein the map representation comprises a four-dimensional map tensor, wherein a first dimension of the map tensor corresponds to the number of the plurality of time steps, a second dimension of the map tensor corresponds to the height of the grid, and a third dimension of the map tensor corresponds to the width of the grid.