Abstract: A computing system and method that can be used for safe and privacy preserving video representations of participants in a videoconference. In particular, the present disclosure provides a general pipeline for generating reconstructions of videoconference participants based on semantic statuses and/or activity statuses of the participants. The systems and methods of the present disclosure allow for videoconferences that convey necessary or meaningful information of participants through presentation of generalized representations of participants while filtering unnecessary or unwanted information from the representations by leveraging machine-learning models.

Abstract: Example implementations of the present disclosure combine efficient model design and dynamic inference. With a standalone lightweight model, the unnecessary computation on easy examples is avoided and the information extracted by the lightweight model also guide the synthesis of a specialist network from the basis models. With extensive experiments on ImageNet it is shown that a proposed example BasisNet is particularly effective for image classification and a BasisNet-MV3 achieves 80.3% top-1 accuracy with 290 M MAdds without early termination.

Abstract: Methods, systems, and apparatus for generating a panoptic segmentation label for a sensor data sample. In one aspect, a system comprises one or more computers configured to obtain a sensor data sample characterizing a scene in an environment. The one or more computers obtain a 3D bounding box annotation at each time point for a point cloud characterizing the scene at the time point. The one or more computers obtain, for each camera image and each time point, annotation data identifying object instances depicted in the camera image, and the one or more computers generate a panoptic segmentation label for the sensor data sample characterizing the scene in the environment.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for audio-visual speech separation. A method includes: receiving, by a user device, a first indication of one or more first speakers visible in a current view recorded by a camera of the user device, in response, generating a respective isolated speech signal for each of the one or more first speakers that isolates speech of the first speaker in the current view and sending the isolated speech signals for each of the one or more first speakers to a listening device operatively coupled to the user device, receiving, by the user device, a second indication of one or more second speakers visible in the current view recorded by the camera of the user device, and in response generating and sending a respective isolated speech signal for each of the one or more second speakers to the listening device.

Abstract: Systems and methods for training a restoration model can leverage training for two sub-tasks to train the restoration model to generate realistic and identity-preserved outputs. The systems and methods can balance the training of the generation task and the reconstruction task to ensure the generated outputs preserve the identity of the original subject while generating realistic outputs. The systems and methods can further leverage a feature quantization model and skip connections to improve the model output and overall training.

Abstract: The present disclosure is directed to systems and methods for performing automated labeling of images. Labeled images can be used to train machine-learned models to infer image attributes such as quality for suggesting user actions.

Abstract: Systems and methods for providing deep learning models capable of performing joint representation learning and new category discovery on a mixture of labeled and unlabeled data, which may include single- and multi-modal data. In some examples, a flexible end-to-end framework uses unified contrastive learning on labeled and unlabeled data based on both instance discrimination and category discrimination, and further uses Winner-Take-All hashing to generate a pseudo-label based on the similarity between each pair of unlabeled data points that can be used to train the model to generate clustering assignments for each unlabeled data point. In some examples, the unified contrastive learning may be further based on cross-modal discrimination.

Abstract: A computing system and method that can be used for safe and privacy preserving video representations of participants in a videoconference. In particular, the present disclosure provides a general pipeline for generating reconstructions of videoconference participants based on semantic statuses and/or activity statuses of the participants. The systems and methods of the present disclosure allow for videoconferences that convey necessary or meaningful information of participants through presentation of generalized representations of participants while filtering unnecessary or unwanted information from the representations by leveraging machine-learning models.

Abstract: A method for quantum key fusion-based virtual power plant security communication includes: identity authentication, performing identity authentication between a client and a server in a virtual power plant based on a communication requirement to acquire a root key; key distribution: generating a key encryption key and a message authentication key based on the acquired root key and performing negotiation on a data encryption key to obtain the data encryption key; and data encryption: encrypting to-be-encrypted data using the data encryption key, and implementing communication of the data. During the identity authentication or the key distribution, negotiation on a quantum key is performed by a quantum key server, and the quantum key obtained by the negotiation is used for implementing the identity authentication or used as the data encryption key. A device for quantum key fusion-based virtual power plant security communication and a computer storage medium are provided.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining neural network architectures. One of the methods includes obtaining training data for a dense image prediction task; and determining an architecture for a neural network configured to perform the dense image prediction task, comprising: searching a space of candidate architectures to identify one or more best performing architectures using the training data, wherein each candidate architecture in the space of candidate architectures comprises (i) the same first neural network backbone that is configured to receive an input image and to process the input image to generate a plurality of feature maps and (ii) a different dense prediction cell configured to process the plurality of feature maps and to generate an output for the dense image prediction task; and determining the architecture for the neural network based on the best performing candidate architectures.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining neural network architectures. One of the methods includes obtaining training data for a dense image prediction task; and determining an architecture for a neural network configured to perform the dense image prediction task, comprising: searching a space of candidate architectures to identify one or more best performing architectures using the training data, wherein each candidate architecture in the space of candidate architectures comprises (i) the same first neural network backbone that is configured to receive an input image and to process the input image to generate a plurality of feature maps and (ii) a different dense prediction cell configured to process the plurality of feature maps and to generate an output for the dense image prediction task; and determining the architecture for the neural network based on the best performing candidate architectures.

Abstract: A method for quantum key fusion-based virtual power plant security communication includes: identity authentication, performing identity authentication between a client and a server in a virtual power plant based on a communication requirement to acquire a root key; key distribution: generating a key encryption key and a message authentication key based on the acquired root key and performing negotiation on a data encryption key to obtain the data encryption key; and data encryption: encrypting to-be-encrypted data using the data encryption key, and implementing communication of the data. During the identity authentication or the key distribution, negotiation on a quantum key is performed by a quantum key server, and the quantum key obtained by the negotiation is used for implementing the identity authentication or used as the data encryption key. A device for quantum key fusion-based virtual power plant security communication and a computer storage medium are provided.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining neural network architectures. One of the methods includes obtaining training data for a dense image prediction task; and determining an architecture for a neural network configured to perform the dense image prediction task, comprising: searching a space of candidate architectures to identify one or more best performing architectures using the training data, wherein each candidate architecture in the space of candidate architectures comprises (i) the same first neural network backbone that is configured to receive an input image and to process the input image to generate a plurality of feature maps and (ii) a different dense prediction cell configured to process the plurality of feature maps and to generate an output for the dense image prediction task; and determining the architecture for the neural network based on the best performing candidate architectures.