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Found 8 papers, 2 papers with code
Unsupervised Multimodal Deepfake Detection Using Intra- and Cross-Modal Inconsistencies
Deepfake videos present an increasing threat to society with potentially negative impact on criminal justice, democracy, and personal safety and privacy.
In-Sensor & Neuromorphic Computing are all you need for Energy Efficient Computer Vision
Although the overhead for the first layer MACs with direct encoding is negligible for deep SNNs and the CV processing is efficient using SNNs, the data transfer between the image sensors and the downstream processing costs significant bandwidth and may dominate the total energy.
P2M-DeTrack: Processing-in-Pixel-in-Memory for Energy-efficient and Real-Time Multi-Object Detection and Tracking
The designs also reduce the sensor and total energy (obtained from in-house circuit simulations at Globalfoundries 22nm technology node) per frame by 5. 7x and 1. 14x, respectively.
P2M: A Processing-in-Pixel-in-Memory Paradigm for Resource-Constrained TinyML Applications
Visual data in such cameras are usually captured in the form of analog voltages by a sensor pixel array, and then converted to the digital domain for subsequent AI processing using analog-to-digital converters (ADC).
Detection and Continual Learning of Novel Face Presentation Attacks
Advances in deep learning, combined with availability of large datasets, have led to impressive improvements in face presentation attack detection research.
Multispectral Biometrics System Framework: Application to Presentation Attack Detection
In this work, we present a general framework for building a biometrics system capable of capturing multispectral data from a series of sensors synchronized with active illumination sources.
Towards Learning Structure via Consensus for Face Segmentation and Parsing
Face segmentation is the task of densely labeling pixels on the face according to their semantics.
Does Generative Face Completion Help Face Recognition?
Face occlusions, covering either the majority or discriminative parts of the face, can break facial perception and produce a drastic loss of information.
