91 citations · 288 across the 14 of their papers we have counts for
5 papers · 1 filter
LookinGood: Enhancing Performance Capture with Real-time Neural Re-Rendering
Ricardo Martin-Brualla, Rohit Pandey, Shuoran Yang +14
Motivated by augmented and virtual reality applications such as telepresence, there has been a recent focus in real-time performance capture of humans under motion. However, given…
MIST: Multiple Instance Spatial Transformer Network
Baptiste Angles, Yuhe Jin, Simon Kornblith +2
We propose a deep network that can be trained to tackle image reconstruction and classification problems that involve detection of multiple object instances, without any supervisio…
SplineNets: Continuous Neural Decision Graphs
Cem Keskin, Shahram Izadi
We present SplineNets, a practical and novel approach for using conditioning in convolutional neural networks (CNNs). SplineNets are continuous generalizations of neural decision g…
StereoNet: Guided Hierarchical Refinement for Real-Time Edge-Aware Depth Prediction
Sameh Khamis, Sean Fanello, Christoph Rhemann +3
This paper presents StereoNet, the first end-to-end deep architecture for real-time stereo matching that runs at 60 fps on an NVidia Titan X, producing high-quality, edge-preserved…
ActiveStereoNet: End-to-End Self-Supervised Learning for Active Stereo Systems
Yinda Zhang, Sameh Khamis, Christoph Rhemann +7
In this paper we present ActiveStereoNet, the first deep learning solution for active stereo systems. Due to the lack of ground truth, our method is fully self-supervised, yet it p…