Physically based rendering of complex scenes can be prohibitively costly...
Recent volumetric 3D reconstruction methods can produce very accurate
re...
We present 3DVNet, a novel multi-view stereo (MVS) depth-prediction meth...
Multimodal classification is a core task in human-centric machine learni...
Rejecting cosmic rays (CRs) is essential for scientific interpretation o...
Deep-learning-based algorithms have led to impressive results in
visual-...
Time-to-contact (TTC), the time for an object to collide with the observ...
Stereo-based depth estimation is a cornerstone of computer vision, with
...
Estimating a mesh from an unordered set of sparse, noisy 3D points is a
...
The ability to estimate the perceptual error between images is an import...
Image hallucination and super-resolution have been studied for decades, ...
We describe a new class of subsampling techniques for CNNs, termed
multi...
Active learning - a class of algorithms that iteratively searches for th...
We present GraphMatch, an approximate yet efficient method for building ...
While RANSAC-based methods are robust to incorrect image correspondences...
Classical ghost imaging has received considerable attention in recent ye...