Deep Learning for HDR Imaging: State-of-the-Art and Future Trends
High dynamic range (HDR) imaging is a technique that allows an extensive dynamic range of exposures, which is important in image processing, computer graphics, and computer vision. In recent years,…
Joint Framework for Single Image Reconstruction and Super-Resolution With an …
Event cameras sense brightness changes in each pixel and yield asynchronous event streams instead of producing intensity images. They have distinct advantages over conventional cameras, such as a h…
E2SRI: Learning to Super-Resolve Intensity Images From Events
An event camera reports per-pixel intensity differences as an asynchronous stream of events with low latency, high dynamic range (HDR), and low power consumption. This stream of sparse/dense events…
Knowledge Distillation and Student-Teacher Learning for Visual Intelligence :…
Deep neural models, in recent years, have been successful in almost every field, even solving the most complex problem statements. However, these models are huge in size with millions (and even bil…
SpherePHD : Applying CNNs on 360∘∘ Images With Non-Euclidean Spherical Po…
Omni-directional images are becoming more prevalent for understanding the scene of all directions around a camera, as they provide a much wider field-of-view (FoV) compared to conventional images. …
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