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Found 4 papers, 1 papers with code
HDR image reconstruction from a single exposure using deep CNNs
We demonstrate that our approach can reconstruct high-resolution visually convincing HDR results in a wide range of situations, and that it generalizes well to reconstruction of images captured with arbitrary and low-end cameras that use unknown camera response functions and post-processing.
Procedural Modeling and Physically Based Rendering for Synthetic Data Generation in Automotive Applications
We present an overview and evaluation of a new, systematic approach for generation of highly realistic, annotated synthetic data for training of deep neural networks in computer vision tasks.
Accelerating pseudo-marginal Metropolis-Hastings by correlating auxiliary variables
Pseudo-marginal Metropolis-Hastings (pmMH) is a powerful method for Bayesian inference in models where the posterior distribution is analytical intractable or computationally costly to evaluate directly.
A Unified Framework for Multi-Sensor HDR Video Reconstruction
We present an implementation in CUDA and show real-time performance for an experimental 4 Mpixel multi-sensor HDR video system.
