Computer-implemented method for determining three-dimensional image information of a scene in the surrounding of a vehicle based on information provided by a camera and a flash LIDAR sensor , the method comprising the steps of: - Receiving image information from the camera , the image information referring to a first coverage area (A) (S10); - Receiving depth information from the flash LIDAR sensor , the depth information referring to a second coverage area (B) being smaller than the first coverage area (A), the first and second coverage areas (A, B) overlapping with each other (S1 1); - Establishing supervised scene information based on the image information and the depth information, the supervised scene information covering the second coverage area (B), wherein the supervised scene information is obtained by predicting depth information based on the image information received from the camera and the depth information provided by the flash LIDAR sensor using a first trained neural network (S12); - Establishing self-supervised scene information based on the image information using a second trained neural network, the self-supervised scene information covering the first coverage area (A), wherein the self-supervised scene information includes depth information, the depth information being predicted by a depth estimation algorithm by considering information included in the image information provided by the camera using photometric loss and/or structural similarity (S13); - Modifying the self-supervised scene information based on the supervised scene information in the first coverage area (A) such that in the overlapping area between the first and second coverage area (A, B), the difference between the depth information included in the self-supervised scene information and the depth information included in the supervised scene information is reduced (S14); - Providing modified depth information based on the modified self-supervised scene information (S15). - Receiving image information from the camera , the image information referring to a first coverage area (A) (S10); - Receiving depth information from the flash LIDAR sensor , the depth information referring to a second coverage area (B) being smaller than the first coverage area (A), the first and second coverage areas (A, B) overlapping with each other (S1 1); - Establishing supervised scene information based on the image information and the depth information, the supervised scene information covering the second coverage area (B), wherein the supervised scene information is obtained by predicting depth information based on the image information received from the camera and the depth information provided by the flash LIDAR sensor using a first trained neural network (S12); - Establishing self-supervised scene information based on the image information using a second trained neural network, the self-supervised scene information covering the first coverage area (A), wherein the self-supervised scene information includes depth information, the depth information being predicted by a depth estimation algorithm by considering information included in the image information provided by the camera using photometric loss and/or structural similarity (S13); - Modifying the self-supervised scene information based on the supervised scene information in the first coverage area (A) such that in the overlapping area between the first and second coverage area (A, B), the difference between the depth information included in the self-supervised scene information and the depth information included in the supervised scene information is reduced (S14); - Providing modified depth information based on the modified self-supervised scene information (S15). <EOS>