Abstract: Methods, systems, apparatus, and articles of manufacture for monocular depth estimation are disclosed. An example apparatus disclosed herein is to determine bin center positions for a pixel of an image based on first features obtained at a first decoder layer of an encoder-decoder architecture, the image representative of a three-dimensional (3D) scene, the bin center positions corresponding to respective different metric depth values. The example apparatus is also to adjust the bin center positions at a second decoder layer of the encoder-decoder architecture based on an attractor point, the attractor point based on the first features and second features obtained at the second decoder layer. The example apparatus is further to output a metric depth map corresponding to the image, the metric depth map including a metric depth value corresponding to the pixel, the metric depth value based on the adjusted bin center positions.

Abstract: A method, apparatus, and non-transitory computer readable medium for image processing are described. Embodiments of the method, apparatus, and non-transitory computer readable medium include identifying an original image including a plurality of semantic attributes, wherein each of the semantic attributes represents a complex set of features of the original image; identifying a target attribute value that indicates a change to a target attribute of the semantic attributes; computing a modified feature vector based on the target attribute value, wherein the modified feature vector incorporates the change to the target attribute while holding at least one preserved attribute of the semantic attributes substantially unchanged; and generating a modified image based on the modified feature vector, wherein the modified image includes the change to the target attribute and retains the at least one preserved attribute from the original image.

Abstract: A method, apparatus, and non-transitory computer readable medium for image processing are described. Embodiments of the method, apparatus, and non-transitory computer readable medium include identifying an original image including a plurality of semantic attributes, wherein each of the semantic attributes represents a complex set of features of the original image; identifying a target attribute value that indicates a change to a target attribute of the semantic attributes; computing a modified feature vector based on the target attribute value, wherein the modified feature vector incorporates the change to the target attribute while holding at least one preserved attribute of the semantic attributes substantially unchanged; and generating a modified image based on the modified feature vector, wherein the modified image includes the change to the target attribute and retains the at least one preserved attribute from the original image.

Abstract: A three-dimensional image reconstruction system includes an image capture device, an inertial measurement unit (IMU), and an image processor. The image capture device captures image data. The inertial measurement unit (IMU) is affixed to the image capture device and records IMU data associated with the image data. The image processor includes one or more processing units and memory for storing instructions that are executed by the one or more processing units, wherein the image processor receives the image data and the IMU data as inputs and utilizes the IMU data to pre-align the first image and the second image, and wherein the image processor utilizes a registration algorithm to register the pre-aligned first and second images.

Abstract: A three-dimensional image reconstruction system includes an image capture device, an inertial measurement unit (IMU), and an image processor. The image capture device captures image data. The inertial measurement unit (IMU) is affixed to the image capture device and records IMU data associated with the image data. The image processor includes one or more processing units and memory for storing instructions that are executed by the one or more processing units, wherein the image processor receives the image data and the IMU data as inputs and utilizes the IMU data to pre-align the first image and the second image, and wherein the image processor utilizes a registration algorithm to register the pre-aligned first and second images.

Abstract: A three-dimensional image reconstruction system includes an image capture device, an inertial measurement unit (IMU), and an image processor. The image capture device captures image data. The inertial measurement unit (IMU) is affixed to the image capture device and records IMU data associated with the image data. The image processor includes one or more processing units and memory for storing instructions that are executed by the one or more processing units, wherein the image processor receives the image data and the IMU data as inputs and utilizes the IMU data to pre-align the first image and the second image, and wherein the image processor utilizes a registration algorithm to register the pre-aligned first and second images.

Abstract: A three-dimensional image reconstruction system includes an image capture device, an inertial measurement unit (IMU), and an image processor. The image capture device captures image data. The inertial measurement unit (IMU) is affixed to the image capture device and records IMU data associated with the image data. The image processor includes one or more processing units and memory for storing instructions that are executed by the one or more processing units, wherein the image processor receives the image data and the IMU data as inputs and utilizes the IMU data to pre-align the first image and the second image, and wherein the image processor utilizes a registration algorithm to register the pre-aligned first and second images.