Intel® AI Visual Inference Samples are easy to use script implementations of workloads with processing pipelines consisting of media and AI inference elements. Samples are built on top of open source ...

Each release of the Intel® AI Visual Inference Samples provides samples for use with a single, specific AI Inference framework. These samples are optimized for best performance with the configurations ...

In natural vision, feedback connections support versatile visual inference capabilities such as making sense of the occluded or noisy bottom-up sensory information or mediating pure top-down processes ...

Imagine walking along in the African savanna. Suddenly you notice a moving bush partially obscuring a large yellow object. From this limited information, you need to figure out if you’re in danger and ...

Humans effortlessly recognize social interactions from visual input. The best models of this ability are generative inverse planning models, which make predictions by simulating agents' inferred goals ...

Computer vision models have made remarkable progress in recent years on fundamental tasks like object recognition and depth estimation — but still struggle with visual queries that require both visual ...

Abstract: We present a hierarchical architecture and learning algorithm for visual recognition and other visual inference tasks such as imagination, reconstruction of occluded images, and ...

Abstract: This paper presents an extensible architecture for the interpretation of visual data and fusion of different sources of information. It is based on a joint inference approach which relies on ...