Abstract: An image stitching method and apparatus are disclosed. The image stitching apparatus includes at least one processor and a memory. The processor may obtain a plurality of images at different viewpoints, estimate homographies of each of the plurality of images, generate an aligned image by aligning the plurality of images based on the homographies of each of the plurality of images, obtain a collective energy map by inputting the aligned image to a neural network, estimate a stitching line of the aligned image based on the collective energy map, and generate a stitched image by blending the aligned image based on the stitching line.

Abstract: An image stitching method and apparatus are disclosed. The image stitching apparatus includes at least one processor and a memory. The processor may obtain a plurality of images at different viewpoints, estimate homographies of each of the plurality of images, generate an aligned image by aligning the plurality of images based on the homographies of each of the plurality of images, obtain a collective energy map by inputting the aligned image to a neural network, estimate a stitching line of the aligned image based on the collective energy map, and generate a stitched image by blending the aligned image based on the stitching line.

Abstract: Systems and methods for estimating a saliency of one or more targets of a drive scene are provided. In some aspects, the system includes a memory that stores instructions for executing processes for estimating the saliency of the one or more targets of the drive scene. The system further includes a processor configured to execute the instructions. In various aspects, the processes include generating a Bayesian framework to model visual attention of a driver, the Bayesian framework comprising a bottom-up saliency element and a top-down saliency element. In various aspects, the processes also include generating a fully convolutional neural network, based on the Bayesian framework, to generate a visual saliency model of the one or more targets in the driving scene. In further aspects, the processes include outputting the visual saliency model to indicate features that attract attention of the driver.