A method for encoding a point cloud, the method comprising: generating, for a three-dimensional, 3D, point cloud, a first two-dimensional, 2D, frame representing a first attribute of the 3D point cloud and a second 2D frame representing a second attribute of the 3D point cloud, wherein the first 2D frame and the second 2D frame include respective clusters of projected points from the 3D point cloud; detecting missed points of the 3D point cloud that are not included in the first 2D frame; generating a first additional points patch representing the first attribute based on a subset of the missed points and a second additional points patch representing the second attribute based on the subset of the missed points; including the first additional points patch in the first 2D frame and the second additional points patch in the second 2D frame; encoding the first 2D frame that include the first additional points patch and the second 2D frame that includes the second additional points patch to generate a compressed bitstream; and transmitting the compressed bitstream, characterised in that the generating of the first additional points patch comprises: identifying a quantity of points within a predefined zone surrounding a respective point of the missed points; for each of the one or more missed points, identifying a distance between the respective point and points within the predefined zone based on a proximity parameter, wherein the proximity parameter indicates the distance between the respective point and the points within the predefined zone based on the first attribute which is a geometry attribute; deriving a neighborhood score by combining an inverse of the identified distances between the respective point and the points within the predefined zone; and generating the first additional points patch by including the respective point in the subset of the one or more missed points if the neighborhood score is greater than or equal to a threshold. generating, for a three-dimensional, 3D, point cloud, a first two-dimensional, 2D, frame representing a first attribute of the 3D point cloud and a second 2D frame representing a second attribute of the 3D point cloud, wherein the first 2D frame and the second 2D frame include respective clusters of projected points from the 3D point cloud; detecting missed points of the 3D point cloud that are not included in the first 2D frame; generating a first additional points patch representing the first attribute based on a subset of the missed points and a second additional points patch representing the second attribute based on the subset of the missed points; including the first additional points patch in the first 2D frame and the second additional points patch in the second 2D frame; encoding the first 2D frame that include the first additional points patch and the second 2D frame that includes the second additional points patch to generate a compressed bitstream; and transmitting the compressed bitstream, characterised in that the generating of the first additional points patch comprises: identifying a quantity of points within a predefined zone surrounding a respective point of the missed points; for each of the one or more missed points, identifying a distance between the respective point and points within the predefined zone based on a proximity parameter, wherein the proximity parameter indicates the distance between the respective point and the points within the predefined zone based on the first attribute which is a geometry attribute; deriving a neighborhood score by combining an inverse of the identified distances between the respective point and the points within the predefined zone; and generating the first additional points patch by including the respective point in the subset of the one or more missed points if the neighborhood score is greater than or equal to a threshold. identifying a quantity of points within a predefined zone surrounding a respective point of the missed points; for each of the one or more missed points, identifying a distance between the respective point and points within the predefined zone based on a proximity parameter, wherein the proximity parameter indicates the distance between the respective point and the points within the predefined zone based on the first attribute which is a geometry attribute; deriving a neighborhood score by combining an inverse of the identified distances between the respective point and the points within the predefined zone; and generating the first additional points patch by including the respective point in the subset of the one or more missed points if the neighborhood score is greater than or equal to a threshold.