A method for monitoring a blind spot of a vehicle, comprising steps of: (a) a blind spot monitor acquiring, or supporting another device to acquire, at least one feature map from a rear video image acquired from a monitoring vehicle in a driving state; (b) the blind spot monitor performing, or supporting another device to perform, (i) a process of acquiring m proposal boxes corresponding to one or more objects located in the rear video image, (ii) a process of acquiring feature vectors each of which corresponds to each of the m proposal boxes by applying pooling operation to each area, on the feature map, corresponding to the m proposal boxes, and (iii) a process of inputting each of the feature vectors corresponding to each of the m proposal boxes into a first fully connected layer to acquire (iii-1) each of first classification scores for each of first kinds of class (S25; S200), which correspond to each of the m proposal boxes, to confirm whether the objects are vehicles (300; 310, 320), and (iii-2) each of second classification scores for each of second kinds of class (S27; S200), which correspond to each of the m proposal boxes, to confirm poses of the objects; and (c) the blind spot monitor performing, or supporting another device to perform, (i) a process of selecting n proposal boxes, which have probabilities over a certain threshold to be regarded as including the vehicles (300; 310, 320), among the m proposal boxes by referring to the first classification scores, (ii) a process of acquiring n bounding boxes, each of which corresponds to each of the n proposal boxes, by referring to regression information corresponding to each of the n proposal boxes, (iii) a process of determining the pose of the vehicles (300; 310, 320) corresponding to each of at least some of the n bounding boxes by referring to the second classification scores, and (iv) a process of determining whether a haphazard vehicle which is one of the vehicles (300; 310, 320) is located in a blind spot of the monitoring vehicle by referring to at least some of the n bounding boxes and the pose of the vehicles (300; 310, 320). (a) a blind spot monitor acquiring, or supporting another device to acquire, at least one feature map from a rear video image acquired from a monitoring vehicle in a driving state; (b) the blind spot monitor performing, or supporting another device to perform, (i) a process of acquiring m proposal boxes corresponding to one or more objects located in the rear video image, (ii) a process of acquiring feature vectors each of which corresponds to each of the m proposal boxes by applying pooling operation to each area, on the feature map, corresponding to the m proposal boxes, and (iii) a process of inputting each of the feature vectors corresponding to each of the m proposal boxes into a first fully connected layer to acquire (iii-1) each of first classification scores for each of first kinds of class (S25; S200), which correspond to each of the m proposal boxes, to confirm whether the objects are vehicles (300; 310, 320), and (iii-2) each of second classification scores for each of second kinds of class (S27; S200), which correspond to each of the m proposal boxes, to confirm poses of the objects; and (c) the blind spot monitor performing, or supporting another device to perform, (i) a process of selecting n proposal boxes, which have probabilities over a certain threshold to be regarded as including the vehicles (300; 310, 320), among the m proposal boxes by referring to the first classification scores, (ii) a process of acquiring n bounding boxes, each of which corresponds to each of the n proposal boxes, by referring to regression information corresponding to each of the n proposal boxes, (iii) a process of determining the pose of the vehicles (300; 310, 320) corresponding to each of at least some of the n bounding boxes by referring to the second classification scores, and (iv) a process of determining whether a haphazard vehicle which is one of the vehicles (300; 310, 320) is located in a blind spot of the monitoring vehicle by referring to at least some of the n bounding boxes and the pose of the vehicles (300; 310, 320).