Abstract: A system and method are described for generating 3D garments from two-dimensional (2D) scribble images drawn by users. The system includes a conditional 2D generator, a conditional 3D generator, and two intermediate media including dimension-coupling color-density pairs and flat point clouds that bridge the gap between dimensions. Given a scribble image, the 2D generator synthesizes dimension-coupling color-density pairs including the RGB projection and density map from the front and rear views of the scribble image. A density-aware sampling algorithm converts the 2D dimension-coupling color-density pairs into a 3D flat point cloud representation, where the depth information is ignored. The 3D generator predicts the depth information from the flat point cloud. Dynamic variations per garment due to deformations resulting from a wearer's pose as well as irregular wrinkles and folds may be bypassed by taking advantage of 2D generative models to bridge the dimension gap in a non-parametric way.

Abstract: An image sensor device includes a semiconductor substrate, a radiation sensing member, a shallow trench isolation, and a color filter layer. The radiation sensing member is in the semiconductor substrate. An interface between the radiation sensing member and the semiconductor substrate includes a direct band gap material. The shallow trench isolation is in the semiconductor substrate and surrounds the radiation sensing member. The color filter layer covers the radiation sensing member.

Abstract: Example methods for generating an animated character in dance poses to music may include generating, by at least one processor, a music input signal based on an acoustic signal associated with the music, and receiving, by the at least one processor, a model output signal from an encoding neural network. A current generated pose data is generated using a decoding neural network, the current generated pose data being based on previous generated pose data of a previous generated pose, the music input signal, and the model output signal. An animated character is generated based on a current generated pose data; and the animated character caused to be displayed by a display device.

Abstract: A system to enable 3D hair reconstruction and rendering from a single reference image which performs a multi-stage process that utilizes both a 3D implicit representation and a 2D parametric embedding space.

Abstract: Systems, computer readable media, and methods herein describe an editing system where a three-dimensional (3D) object can be edited by editing a 2D sketch or 2D RGB views of the 3D object. The editing system uses multi-modal (MM) variational auto-decoders (VADs)(MM-VADs) that are trained with a shared latent space that enables editing 3D objects by editing 2D sketches of the 3D objects. The system determines a latent code that corresponds to an edited or sketched 2D sketch. The latent code is then used to generate a 3D object using the MM-VADs with the latent code as input. The latent space is divided into a latent space for shapes and a latent space for colors. The MM-VADs are trained with variational auto-encoders (VAE) and a ground truth.

Abstract: Example methods for generating an animated character in dance poses to music may include generating, by at least one processor, a music input signal based on an acoustic signal associated with the music, and receiving, by the at least one processor, a model output signal from an encoding neural network. A current generated pose data is generated using a decoding neural network, the current generated pose data being based on previous generated pose data of a previous generated pose, the music input signal, and the model output signal. An animated character is generated based on a current generated pose data; and the animated character caused to be displayed by a display device.

Abstract: A multimodal video generation framework (MMVID) that benefits from text and images provided jointly or separately as input. Quantized representations of videos are utilized with a bidirectional transformer with multiple modalities as inputs to predict a discrete video representation. A new video token trained with self-learning and an improved mask-prediction algorithm for sampling video tokens is used to improve video quality and consistency. Text augmentation is utilized to improve the robustness of the textual representation and diversity of generated videos. The framework incorporates various visual modalities, such as segmentation masks, drawings, and partially occluded images. In addition, the MMVID extracts visual information as suggested by a textual prompt.

Abstract: Example methods for generating an animated character in dance poses to music may include generating, by at least one processor, a music input signal based on an acoustic signal associated with the music, and receiving, by the at least one processor, a model output signal from an encoding neural network. A current generated pose data is generated using a decoding neural network, the current generated pose data being based on previous generated pose data of a previous generated pose, the music input signal, and the model output signal. An animated character is generated based on a current generated pose data; and the animated character caused to be displayed by a display device.

Abstract: Computer vision systems and methods for image to image translation are provided. The system receives a first input image and a second input image and applies a content adversarial loss function to the first input image and the second input image to determine a disentanglement representation of the first input image and a disentanglement representation of the second input image. The system trains a network to generate at least one output image by applying a cross cycle consistency loss function to the first disentanglement representation and the second disentanglement representation to perform multimodal mapping between the first input image and the second input image.

Abstract: Systems and methods for unsupervised representation learning by sorting sequences are provided. An unsupervised representation learning approach is provided which uses videos without semantic labels. The temporal coherence as a supervisory signal can be leveraged by formulating representation learning as a sequence sorting task. A plurality of temporally shuffled frames (i.e., in non-chronological order) can be used as inputs and a convolutional neural network can be trained to sort the shuffled sequences and to facilitate machine learning of features by the convolutional neural network. Features are extracted from all frame pairs and aggregated to predict the correct sequence order. As sorting shuffled image sequence requires an understanding of the statistical temporal structure of images, training with such a proxy task can allow a computer to learn rich and generalizable visual representations from digital images.

Abstract: Aspects of the disclosure provide a control apparatus that includes transceiver circuitry and processing circuitry. The transceiver circuitry is configured to transmit/receive signals from a plurality of terminal devices using a shared channel. The processing circuitry is configured to determine distances to the plurality of terminal devices, allocate resource elements in the shared channel according to the distances, and communicate, via the transceiver circuitry, with the plurality of terminal devices according to the allocation of the resource elements in the shared channel.

Abstract: Aspects of the disclosure provide a control apparatus that includes transceiver circuitry and processing circuitry. The transceiver circuitry is configured to transmit/receive signals from a plurality of terminal devices using a shared channel. The processing circuitry is configured to determine distances to the plurality of terminal devices, allocate resource elements in the shared channel according to the distances, and communicate, via the transceiver circuitry, with the plurality of terminal devices according to the allocation of the resource elements in the shared channel.

Abstract: A method of UE category and capability indication for co-existed 4G LTE and 5G New Ratio (NR) devices is proposed. UE indicates UE category and associated capability for standalone NR, which includes band combination for NR and a list of capability combinations of baseband feature sets. UE also indicates separate UE category and associated capability for 5G NR EN-DC (EUTRA-NR Dual Connectivity), which includes band combination for NR+LTE, and a list of capability combinations of baseband feature sets. Based on such indication, the network can enable the UE to operate over multiple connections via multiple radio access technology (RATs) concurrently. In one novel aspect, the baseband feature set combination is band combination agnostic.

Abstract: A biosensor structure is provided, which includes a substrate, a center conductor, a first ground conductor, a second ground conductor and a protection layer. The center conductor is disposed on the substrate and defines a detection area at the central area thereof for detection of cells or biomolecules. The first ground conductor is disposed on the substrate and is located opposite to a side of the center conductor. The second ground conductor is disposed on the substrate and is located opposite to another side of the center conductor. The protection layer is disposed on the substrate, the center conductor, the first ground conductor and the second ground conductor. In a thickness direction of the biosensor structure, the protection layer is disposed without substantially overlapping the detection area.

Abstract: An electronic device includes a circuit board. The circuit board includes a power amplifier footprint configured for mounting a first power amplifier or a second power amplifier thereon. The power amplifier footprint includes a first part and a second part. The first part includes multiple I/O pads. When the first power amplifier is mounted on the circuit board, the I/O pads in the first part are coupled to the first power amplifier. The second part includes multiple I/O pads. When the second power amplifier is mounted on the circuit board, both the I/O pads in the first part and the I/O pads in the second part are coupled to the second power amplifier.

Abstract: Disclosure is a biosensor chip having precise count function comprising: a substrate, a plurality of ground wire waveguide layers, a signal waveguide layer and a protective layer. Wherein, the plurality of ground wire waveguide layers are located on two sides of the substrate, the signal waveguide layer is located on the substrate and between the plurality of ground wire waveguide layers, wherein the signal waveguide layer has a recess which forms a cell sensing region; and the protective layer covers a portion of the ground wire waveguide layers and a portion of the signal waveguide layer to expose the recess.

Abstract: A processing machine that combines the functions of mounting press and grinding for metallographic analysis and includes a main frame at least one shaft and a drive device horizontally mounted on the main frame. A mounting press unit and a grind unit are mounted on the main frame. The grind unit including a base secured on the main frame and linearly corresponds to the mounting press unit and the corresponding line parallel to the at least one shaft. The grind unit includes a headstock slidably mounted on the at least one shaft the and reciprocally moved on the at least one shaft to selectively align with the base of the grind unit and the mounting press unit when the drive device is operated. A control unit disposed in the grind unit for controlling the mounting press unit and the grind unit.

Abstract: A radio frequency (RF) module capable of self-calibration is provided. According to an embodiment, the RF module includes an RF signal processor, a plurality of RF signal paths, an antenna switch module (ASM), and a power detector. The RF signal paths are connected between the RF signal processor and the ASM. The ASM has an antenna port and selectively connects the RF signal processor to the antenna port through one of the RF signal paths. The power detector is operative to detect power of an RF transmission signal that exits the antenna port of the ASM and enters an antenna when the ASM connects an RF transmission path of the RF signal paths to the antenna port of the ASM.

Abstract: A processing machine that combines the functions of mounting press and grinding for metallographic analysis and includes a main frame at least one shaft and a drive device horizontally mounted on the main frame. A mounting press unit and a grind unit are mounted on the main frame. The grind unit including a base secured on the main frame and linearly corresponds to the mounting press unit and the corresponding line parallel to the at least one shaft. The grind unit includes a headstock slidably mounted on the at least one shaft the and reciprocally moved on the at least one shaft to selectively align with the base of the grind unit and the mounting press unit when the drive device is operated. A control unit disposed in the grind unit for controlling the mounting press unit and the grind unit.

Abstract: A radio frequency (RF) module capable of self-calibration is provided. According to an embodiment, the RF module includes an RF signal processor, a plurality of RF signal paths, an antenna switch module (ASM), and a power detector. The RF signal paths are connected between the RF signal processor and the ASM. The ASM has an antenna port and selectively connects the RF signal processor to the antenna port through one of the RF signal paths. The power detector is operative to detect power of an RF transmission signal that exits the antenna port of the ASM and enters an antenna when the ASM connects an RF transmission path of the RF signal paths to the antenna port of the ASM.