A method for determining the pose of a target object in an input image, comprising the steps of: • providing a set of reference images that contain the target object and are annotated with the respective pose (2a*) of the target object; • inputting the reference images to at least one segmentor (10, 11) that is configured to distinguish parts and/or features of an image belonging to different objects, wherein the at least one segmentor (10, 11) comprises: a first, coarse segmentor φ that is configured to determine sets of pixels of the image belonging to different objects, and a second, dense segmentor φ * that is configured to determine a set of features for each pixel of the image; • determining, from the output (10a, 11a) of the at least one segmentor (10, 11), a canonical object model that pools information from the reference images in one common coordinate system; • determining, from the output (10a, 11a) of the at least one segmentor (10, 11) in combination with the annotation (2a*) of the reference images, a representation of the target object in the output space of at least one segmentor (10, 11), characterized in that the determining of the representation of the target object comprises: determining, for each set of pixels belonging to an object according to the coarse segmentor φ, based on the annotation (2a*) of the respective reference image, whether this set of pixels belongs to the target object; if the set of pixels belongs to the target object, computing an aggregate of the features outputted by the dense segmentor φ * over all pixels in the set as a positive object-level representation; and computing an aggregate of the positive object level representations as the representation of the target object; • inputting the input image to the at least one segmentor (10, 11), and determining, based on a comparison of the resulting output (10b, 11b) of the at least one segmentor (10, 11) and the representation of the target object, which parts (10c, 11c) of said resulting output (10b, 11b) of the at least one segmentor (10, 11) belong to the target object; • combining said parts (10c, 11c) belonging to the target object into a local reconstruction of the target object; and • evaluating, from a comparison of the local reconstruction and the canonical object model, the sought pose of the target object in the input image. • providing a set of reference images that contain the target object and are annotated with the respective pose (2a*) of the target object; • inputting the reference images to at least one segmentor (10, 11) that is configured to distinguish parts and/or features of an image belonging to different objects, wherein the at least one segmentor (10, 11) comprises: a first, coarse segmentor φ that is configured to determine sets of pixels of the image belonging to different objects, and a second, dense segmentor φ * that is configured to determine a set of features for each pixel of the image; • determining, from the output (10a, 11a) of the at least one segmentor (10, 11), a canonical object model that pools information from the reference images in one common coordinate system; • determining, from the output (10a, 11a) of the at least one segmentor (10, 11) in combination with the annotation (2a*) of the reference images, a representation of the target object in the output space of at least one segmentor (10, 11), characterized in that the determining of the representation of the target object comprises: determining, for each set of pixels belonging to an object according to the coarse segmentor φ, based on the annotation (2a*) of the respective reference image, whether this set of pixels belongs to the target object; if the set of pixels belongs to the target object, computing an aggregate of the features outputted by the dense segmentor φ * over all pixels in the set as a positive object-level representation; and computing an aggregate of the positive object level representations as the representation of the target object; determining, for each set of pixels belonging to an object according to the coarse segmentor φ, based on the annotation (2a*) of the respective reference image, whether this set of pixels belongs to the target object; if the set of pixels belongs to the target object, computing an aggregate of the features outputted by the dense segmentor φ * over all pixels in the set as a positive object-level representation; and computing an aggregate of the positive object level representations as the representation of the target object; • inputting the input image to the at least one segmentor (10, 11), and determining, based on a comparison of the resulting output (10b, 11b) of the at least one segmentor (10, 11) and the representation of the target object, which parts (10c, 11c) of said resulting output (10b, 11b) of the at least one segmentor (10, 11) belong to the target object; • combining said parts (10c, 11c) belonging to the target object into a local reconstruction of the target object; and • evaluating, from a comparison of the local reconstruction and the canonical object model, the sought pose of the target object in the input image.