Abstract: Embodiments of the present disclosure provides a method, apparatus, electronic device, computer readable storage medium, computer program product and computer program for image restoration. The method comprises: in response to a selection operation of a user in any region of an image to be restored within an image restoration page, determining a first target region selected by the user; generating, based on the first target region, a first region associated with the first target region, and displaying a predetermined editing page in the image restoration page; in response to editing content input by the user in the editing page, editing the first region based on the editing content to obtain a second region; and performing, based on the second region, an image restoration operation on the image to be restored.

Abstract: A system of integrated water and fertilizer planting and industrial collaboration for a terraced field in an ecologically fragile area includes a hardware part, a software part, a water balance and osmosis model, a water and fertilizer optimization and adjustment model, and an industry collaboration model. The hardware part includes a terraced field intelligent irrigation equipment, soil moisture sensors, a meteorological station, a fertilizer application device, an underground water storage system, and a solar power supply. The system introduces the water balance and osmosis model to effectively manage water resources in terraced field. By integrating data from the soil sensors and meteorological station, it automatically optimizes the methods of irrigation and fertilization, preventing water waste and soil erosion.

Abstract: A vehicle, system and method of aligning a first camera of the vehicle with a second camera of the vehicle. The system includes a processor configured to detect a first set of features in a first image obtained from the first camera, detect a second set of features in a second image obtained from the second camera, determine a first region of interest in the first image, determine a second region of interest in the second image, generate a feature pair by matching the first set of features to the second set of features using the first region of interest and the second region of interest, align the first camera with the second camera using the feature pair, and control an operation at the vehicle based on the alignment between the first camera and the second camera.

Abstract: A method of performing a camera to ground alignment for a camera system on a vehicle. The method includes determining if enabling conditions have occurred and estimating a location of a vanishing point in a source image. Ground lines are selected based on a source image. A lane line detection is performed based on clustering of the ground lines to determine lane lines in the source image. At least one of pitch, yaw, or roll of the vehicle are estimated from the source image. A cost function based on estimates of pitch, yaw, and roll is minimized to obtain an optimal pitch value, an optimal yaw value, an optimal roll value, and lane lines from the source image. A sliding window-based refinement is performed on source images. Alignment results are broadcast to a downstream application or it is determined if the camera system on the vehicle is misaligned.

Abstract: A computer-implemented method for aligning a sensor to a vehicle includes receiving a first frame of measurement from the sensor which includes a first point cloud. One or more clusters Ci representing one or more objects or the ground are segmented. A first set of feature vectors fi is computed for each cluster Ci. Based on the first set of feature vectors fi a second set of feature vectors fi? is predicted respectively using an initial transformation. A third set of feature vectors fj is computed for a second frame with a second point cloud with clusters Cj. A pair of matching clusters is identified from Ci and Cj. A feature distance between the matching clusters is computed. An alignment transformation is computed by updating the initial transformation based on the feature distance. The method further includes aligning the sensor and the vehicle based on the alignment transformation.

Abstract: A driving circuit of a display panel is provided. The display panel includes sensing electrodes. The driving circuit includes a first control unit and a compensation control unit. The first control unit outputs a common voltage or a modulation voltage to the sensing electrodes. The compensation control unit is electrically connected to an input signal line and the first control unit. In a display stage, the compensation control unit generates a first voltage signal according to a feedback signal and an input signal transmitted by the input signal line, and the first control unit outputs the common voltage according to the first voltage signal. In a sensing stage, the compensation control unit generates a second voltage signal according to the input signal, and the first control unit outputs the modulation voltage according to the second voltage signal.

Abstract: A system and method for system learning updates for online sensor alignment includes receiving sensor data detected by a sensor system of a vehicle, generating, using a coordinate transformation matrix (CTM), a sensor alignment result, and determining, based on a degradation detection model, that a deviation between the sensor alignment result and one or more of a fleet model, a vehicle model, and a system model exceeds an onboard degradation threshold. The system and method also includes determining, based on an offline degradation model, that a deviation between the sensor alignment result and an offline model result exceeds an offline degradation threshold, and triggering corner case data collection to collect additional sensor data detected by the sensor system of the vehicle.

Abstract: A computer-implemented method for aligning a sensor to reference coordinate system includes initiating a plurality of threads, each thread executes simultaneously and independent of each other. A first thread parses data received from the sensor and stores the parsed data in a data buffer. A second thread computes an alignment transformation using the parsed data to determine alignment between the sensor and the reference coordinate system. The computing includes checking that the data buffer contains at least predetermined amount of data. If at least the predetermined amount of data exists, an intermediate result is computed using the parsed data in the data buffer; otherwise, the second thread waits for the first thread to add more data to the data buffer. The second thread outputs the intermediate result into the data buffer. A third thread outputs the alignment transformation, in response to completion of alignment computations.

Abstract: Key phrase generation using indefinite sequence learning is described. In accordance with the described techniques, a sequence generation model generates a sequence of key phrases based on an input document. During the generation task, the sequence generation model omits use of a self-generated sequence termination token. Key phrases in the sequence are then output as recommended key phrases for the input document.

Abstract: A dataset is received that includes items listed via a listing platform, titles of the items, and key phrases. Each of the items are paired with one or more of the key phrases in the dataset. A data structure is constructed that maps tokens of the titles to the items associated with the titles, and maps the items to the key phrases that are paired with the items in the dataset. A seed title of a seed item is received as listed via the listing platform, and the seed title includes seed tokens. One or more similar items to the seed item are identified based on occurrence counts of the one or more seed tokens that map to the one or more similar items in the data structure. At least one recommended key phrase is output that maps to the one or more similar items in the data structure.

Abstract: A vehicle includes a system performing a method of operating a camera for the vehicle. The camera is configured to capture an image. The processor is configured to query the camera to obtain an intrinsic parameter of the camera, estimate a unified parameter based on the intrinsic parameter of the camera, and perform at least one application on the image using the unified parameter.

Abstract: A vehicle includes a system that performs a method for aligning a first camera and a second camera to a reference frame of the vehicle. The first camera has a first coordinate system, and the second camera has a second coordinate system. The first camera obtains a first image. The processor is configured to obtain a first camera-to-ground transformation matrix for the first camera using the first image, wherein the first camera-to-ground transformation matrix relates the first coordinate system to a ground coordinate system, obtain a camera-to-camera transformation matrix between the first coordinate system of the first camera and the second coordinate system of the second camera, calculate a constructed camera-to-ground transformation matrix for the second camera using the first camera-to-ground transformation matrix and the camera-to-camera transformation matrix, and update the second coordinate system of the second camera using the constructed camera-to-ground transformation.

Abstract: A system includes a platform operational to move through an environment, a navigation system operational to measure platform poses of the platform in the environment, a camera operational to generate images of the environment at multiple timestamps, and a computer. The computer is operational to receive a first image from the camera, receive a second image from the camera, estimate a view direction of the first camera pose based on a first and second platform poses and alignment parameters, generate a rendered portion of the environment with a neural radiance field technique based on the second image and the alignment parameters, generate a predicted image of the environment as observed along the view direction through the rendered portion of the environment, determine differences between the first image and the predicted image, and update one or more of the plurality of alignment parameters based on the one or more differences.

Abstract: Disclosed in the embodiments of the present disclosure are a video generation method, an apparatus, an electronic device and a storage medium. The method comprises: during an image editing process of subjecting an initial image to a series of image editing operations to obtain a target image, acquiring initial key frames, the initial key frames being intermediate images between the initial image and the target image during the image editing process, the different initial key frames being intermediate images generated when different image editing operations of the series of image editing operations are triggered during the image editing process, and the intermediate images showing editing effects corresponding to the image editing operations; and generating a target video according to the initial key frames so as to record the image editing process of the target image. The present disclosure can be used for recording an image editing process.

Abstract: A camera misalignment detection system detecting a misalignment condition of one or more cameras for a vehicle includes one or more controllers that determine a set of matched pixel pairs, determine a feature matching ratio based on the set of matched pixel pairs, and calculate an alignment angle difference of the one or more cameras. In response to determining the feature matching ratio, the essential matrix inlier ratio, and the alignment angle difference each exceed respective threshold values, the controllers add the alignment angle difference to a queue including a sequence of historical alignment angle difference values. The controllers perform statistical filtering to determine a total number of historical alignment angle difference values within the queue that are inliers and determine a misalignment condition of the one or more cameras based on the total number of historical alignment angle difference values within the queue that are inliers.

Abstract: A system includes a platform operational to move through an environment, a navigation system operational to measure platform poses of the platform in the environment, a camera operational to generate images of the environment at multiple timestamps, and a computer. The computer is operational to receive a first image from the camera, receive a second image from the camera, estimate a view direction of the first camera pose based on a first and second platform poses and alignment parameters, generate a rendered portion of the environment with a neural radiance field technique based on the second image and the alignment parameters, generate a predicted image of the environment as observed along the view direction through the rendered portion of the environment, determine differences between the first image and the predicted image, and update one or more of the plurality of alignment parameters based on the one or more differences.

Abstract: A driving circuit of a display panel is provided. The display panel includes sensing electrodes. The driving circuit includes a first control unit and a compensation control unit. The first control unit outputs a common voltage or a modulation voltage to the sensing electrodes. The compensation control unit is electrically connected to an input signal line and the first control unit. In a display stage, the compensation control unit generates a first voltage signal according to a feedback signal and an input signal transmitted by the input signal line, and the first control unit outputs the common voltage according to the first voltage signal. In a sensing stage, the compensation control unit generates a second voltage signal according to the input signal, and the first control unit outputs the modulation voltage according to the second voltage signal.

Abstract: A method of performing a camera to ground alignment for a camera system on a vehicle. The method includes determining if enabling conditions have occurred and estimating a location of a vanishing point in a source image. Ground lines are selected based on a source image. A lane line detection is performed based on clustering of the ground lines to determine lane lines in the source image. At least one of pitch, yaw, or roll of the vehicle are estimated from the source image. A cost function based on estimates of pitch, yaw, and roll is minimized to obtain an optimal pitch value, an optimal yaw value, an optimal roll value, and lane lines from the source image. A sliding window-based refinement is performed on source images. Alignment results are broadcast to a downstream application or it is determined if the camera system on the vehicle is misaligned.

Abstract: A vehicle, a system and a method of navigating the vehicle. The system includes a camera conveyed by the vehicle and a processor. The camera is configured to obtain an original image data file of an environment. The processor is configured to reduce the original image data file to obtain a reduced image data file and determine an alignment between a camera-centered coordinate system and a ground coordinate system using the reduced image data file.

Abstract: Disclosed in the embodiments of the present disclosure are a video generation method, an apparatus, an electronic device and a storage medium. The method comprises: during an image editing process of subjecting an initial image to a series of image editing operations to obtain a target image, acquiring initial key frames, the initial key frames being intermediate images between the initial image and the target image during the image editing process, the different initial key frames being intermediate images generated when different image editing operations of the series of image editing operations are triggered during the image editing process, and the intermediate images showing editing effects corresponding to the image editing operations; and generating a target video according to the initial key frames so as to record the image editing process of the target image. The present disclosure can be used for recording an image editing process.