Abstract: The present disclosure provides a driving device, a bucket and a vending machine. The driving device comprises a base, a motor arranged on the base, a transmission mechanism in transmission connection with the output shaft of the motor and a power output wheel in transmission connection with the transmission mechanism; the transmission mechanism is configured to drive the power output wheel to rotate and to move from a first position to a second position when the output shaft of the motor rotates in a first preset direction; the transmission mechanism is also configured to drive the power output wheel to move from the second position to the first position when the output shaft of the motor rotates in a second preset direction; wherein the first preset direction is opposite to the second preset direction.

Abstract: Presented herein are embodiments of a vision-based object perception system for activity analysis, safety monitoring, or both. Embodiments of the perception subsystem detect multi-class objects (e.g., construction machines and humans) in real-time while estimating the poses and actions of the detected objects. Safety monitoring embodiments and object activity analysis embodiments may be based on the perception result. To evaluate the performance of embodiments, a dataset was collected including multi-class of objects in different lighting conditions with human annotations. Experimental results show that the proposed action recognition approach outperforms the state-of-the-art approaches on top-1 accuracy by about 5.18%.

Abstract: Presented herein are novel approaches to synthesize video of the speech from text. In a training phase, embodiments build a phoneme-pose dictionary and train a generative neural network model using a generative adversarial network (GAN) to generate video from interpolated phoneme poses. In deployment, the trained generative neural network in conjunction with the phoneme-pose dictionary convert an input text into a video of a person speaking the words of the input text. Compared to audio-driven video generation approaches, the embodiments herein have a number of advantages: 1) they only need a fraction of the training data used by an audio-driven approach; 2) they are more flexible and not subject to vulnerability due to speaker variation; and 3) they significantly reduce the preprocessing, training, and inference times.

Abstract: Presented herein are novel embodiments for converting a given speech audio or text into a photo-realistic speaking video of a person with synchronized, realistic, and expressive body dynamics. In one or more embodiments, 3D skeleton movements are generated from the audio sequence using a recurrent neural network, and an output video is synthesized via a conditional generative adversarial network. To make movements realistic and expressive, the knowledge of an articulated 3D human skeleton and a learned dictionary of personal speech iconic gestures may be embedded into the generation process in both learning and testing pipelines. The former prevents the generation of unreasonable body distortion, while the later helps the model quickly learn meaningful body movement with a few videos. To produce photo-realistic and high-resolution video with motion details, a part-attention mechanism is inserted in the conditional GAN, where each detailed part is automatically zoomed in to have their own discriminators.

Abstract: Systems and methods of video inpainting for autonomous driving are disclosed. For example, the method stitches a multiplicity of depth frames into a 3D map, where one or more objects in the depth frames have previously been removed. The method further projects the 3D map onto a first image frame to generate a corresponding depth map, where the first image frame includes a target inpainting region. For each target pixel within the target inpainting region of the first image frame, based on the corresponding depth map, the method further maps the target pixel within the target inpainting region of the first image frame to a candidate pixel in a second image frame. The method further determines a candidate color to fill the target pixel. The method further performs Poisson image editing on the first image frame to achieve color consistency at a boundary and between inside and outside of the target inpainting region of the first image frame.

Abstract: Presented herein are novel approaches to synthesize video of the speech from text. In a training phase, embodiments build a phoneme-pose dictionary and train a generative neural network model using a generative adversarial network (GAN) to generate video from interpolated phoneme poses. In deployment, the trained generative neural network in conjunction with the phoneme-pose dictionary convert an input text into a video of a person speaking the words of the input text. Compared to audio-driven video generation approaches, the embodiments herein have a number of advantages: 1) they only need a fraction of the training data used by an audio-driven approach; 2) they are more flexible and not subject to vulnerability due to speaker variation; and 3) they significantly reduce the preprocessing, training, and inference times.

Abstract: Presented herein are novel embodiments for converting a given speech audio or text into a photo-realistic speaking video of a person with synchronized, realistic, and expressive body dynamics. In one or more embodiments, 3D skeleton movements are generated from the audio sequence using a recurrent neural network, and an output video is synthesized via a conditional generative adversarial network. To make movements realistic and expressive, the knowledge of an articulated 3D human skeleton and a learned dictionary of personal speech iconic gestures may be embedded into the generation process in both learning and testing pipelines. The former prevents the generation of unreasonable body distortion, while the later helps the model quickly learn meaningful body movement with a few videos. To produce photo-realistic and high-resolution video with motion details, a part-attention mechanism is inserted in the conditional GAN, where each detailed part is automatically zoomed in to have their own discriminators.

Abstract: Systems and methods of video inpainting for autonomous driving are disclosed. For example, the method stitches a multiplicity of depth frames into a 3D map, where one or more objects in the depth frames have previously been removed. The method further projects the 3D map onto a first image frame to generate a corresponding depth map, where the first image frame includes a target inpainting region. For each target pixel within the target inpainting region of the first image frame, based on the corresponding depth map, the method further maps the target pixel within the target inpainting region of the first image frame to a candidate pixel in a second image frame. The method further determines a candidate color to fill the target pixel. The method further performs Poisson image editing on the first image frame to achieve color consistency at a boundary and between inside and outside of the target inpainting region of the first image frame.

Abstract: The present disclosure provides a driving device, a bucket and a vending machine. The driving device comprises a base, a motor arranged on the base, a transmission mechanism in transmission connection with the output shaft of the motor and a power output wheel in transmission connection with the transmission mechanism; the transmission mechanism is configured to drive the power output wheel to rotate and to move from a first position to a second position when the output shaft of the motor rotates in a first preset direction; the transmission mechanism is also configured to drive the power output wheel to move from the second position to the first position when the output shaft of the motor rotates in a second preset direction; wherein the first preset direction is opposite to the second preset direction.

Abstract: An intravenous catheter securement device comprises of an intravenous catheter board stabilizer that conforms to patients' bodies and an adjustable elastic sleeve with a hole for catheter insertion, with two overlying flaps for catheter securement. The intravenous catheter board base has holes on either side, one side for connection of the elastic sleeve, and the other side provides a fastening location for elastic bands attached to the sleeve for tightness adjustment. An embodiment of the invention involving the intravenous board is displayed separately as an alternative innovation. This device is comprised of a simple form fitting elastic sleeve having a catheter opening with the intent of applying a removable adhesive to the sleeve itself over the catheter for securement purposes. These embodiments establish a simple, standardized, and safe method of securing intravenous catheters sans adhesive material in contact with the epidermis.

Abstract: An intravenous catheter securement device comprises of an intravenous catheter board stabilizer that conforms to patients' bodies and an adjustable elastic sleeve with a hole for catheter insertion, with two overlying flaps for catheter securement. The intravenous catheter hoard base has holes on either side, one side for connection of the elastic sleeve, and the other side provides a fastening location for elastic bands attached to the sleeve for tightness adjustment. An embodiment of the invention involving the intravenous board is displayed separately as an alternative innovation. This device is comprised of a simple form fitting elastic sleeve having a catheter opening with the intent of applying a removable adhesive to the sleeve itself over the catheter for securement purposes. These embodiments establish a simple, standardized, and safe method of securing intravenous catheters sans adhesive material in contact with the epidermis.