33 citations · 58 across the 6 of their papers we have counts for
7 papers
Fast Monocular Scene Reconstruction with Global-Sparse Local-Dense Grids
Wei Dong, Chris Choy, Charles Loop +3
Indoor scene reconstruction from monocular images has long been sought after by augmented reality and robotics developers. Recent advances in neural field representations and monoc…
RGB-Only Reconstruction of Tabletop Scenes for Collision-Free Manipulator Control
Zhenggang Tang, Balakumar Sundaralingam, Jonathan Tremblay +6
We present a system for collision-free control of a robot manipulator that uses only RGB views of the world. Perceptual input of a tabletop scene is provided by multiple images of…
RTMV: A Ray-Traced Multi-View Synthetic Dataset for Novel View Synthesis
Jonathan Tremblay, Moustafa Meshry, Alex Evans +9
We present a large-scale synthetic dataset for novel view synthesis consisting of ~300k images rendered from nearly 2000 complex scenes using high-quality ray tracing at high resol…
Neural Geometric Level of Detail: Real-time Rendering with Implicit 3D Shapes
Towaki Takikawa, Joey Litalien, Kangxue Yin +6
Neural signed distance functions (SDFs) are emerging as an effective representation for 3D shapes. State-of-the-art methods typically encode the SDF with a large, fixed-size neural…
Displacement-Invariant Cost Computation for Efficient Stereo Matching
Yiran Zhong, Charles Loop, Wonmin Byeon +7
Although deep learning-based methods have dominated stereo matching leaderboards by yielding unprecedented disparity accuracy, their inference time is typically slow, on the order…
Improving Deep Stereo Network Generalization with Geometric Priors
Jialiang Wang, Varun Jampani, Deqing Sun +3
End-to-end deep learning methods have advanced stereo vision in recent years and obtained excellent results when the training and test data are similar. However, large datasets of…