We propose a CNN-based approach for reconstructing HDR images from just a single exposure. It predicts the saturated areas of LDR images and then blends the linearized input with the predicted outputs. Two loss functions ...

Recently, disparity-based 3D reconstruction for stereo camera pairs and light field cameras have been greatly improved with the uprising of deep learning-based methods. However, only few of these approaches address ...

We propose to explore a GPU solution to the fixed-radius nearest-neighbor problem in 2D based on Delaunay triangulations. This problem is crucial for many particle-based simulation techniques for collision detection or ...

Heightmaps are ubiquitous in real-time computer graphics. They are used to describe geometric detail over an underlying coarser surface. Various techniques, such as parallax occlusion mapping and relief mapping, use heightmap ...

Autonomous Vehicles became every day closer to becoming a reality in ground transportation. Computational advancement has enabled powerful methods to process large amounts of data required to drive on streets safely. The ...

Learning a 3D representation of a scene has been a challenging problem for decades in computer vision. Recent advancements in implicit neural representation from images using neural radiance fields(NeRF) have shown promising ...

We introduce a new method to compute the shape of an unstructured set of two-dimensional points. The algorithm exploits the to-date rarely used proximity-based graph called spheres-of-influence graph (SIG). We filter edges ...

Creating a 2D animation with visible strokes is a tedious and time consuming task for an artist. Computer aided animation usually focus on cartoon stylized rendering, or is built from an automatic process as 3D animations ...

Precomputed Radiance Transfer (PRT) can achieve high-quality renders of glossy materials at real-time framerates. PRT involves precomputing a k-dimensional transfer vector or a k×k- matrix of Spherical Harmonic (SH) ...