4 citations · 10 across the 18 of their papers we have counts for
14 papers · 1 filter
VCURF: Virtual Camera-based Uncertainty of Radiance Fields
Liyan Chen, Nathaniel Burgdorfer, Philippos Mordohai
Radiance fields, implemented with either implicit (NeRF) or explicit (Gaussian Splatting) representations, are advancing the state of the art in novel view synthesis at a rapid pac…
TV-SGS: Gaussian Splatting with Geometric Information Propagation via Tensor Voting under sparse views
Harish N Sathishchandra, Philippos Mordohai
Gaussian Splatting has been effective in inferring scene representations that excel in novel view synthesis. Multiple splats cooperate seamlessly to synthesize the pixels of novel…
Radiant Triangle Soup with Soft Connectivity Forces for 3D Reconstruction and Novel View Synthesis
Nathaniel Burgdorfer, Philippos Mordohai
We introduce an inference-time scene optimization algorithm utilizing triangle soup, a collection of disconnected translucent triangle primitives, as the representation for the geo…
Glissando-Net: Deep sinGLe vIew category level poSe eStimation ANd 3D recOnstruction
Bo Sun, Hao Kang, Li Guan +3
We present a deep learning model, dubbed Glissando-Net, to simultaneously estimate the pose and reconstruct the 3D shape of objects at the category level from a single RGB image. P…
V-FUSE: Volumetric Depth Map Fusion with Long-Range Constraints
Nathaniel Burgdorfer, Philippos Mordohai
We introduce a learning-based depth map fusion framework that accepts a set of depth and confidence maps generated by a Multi-View Stereo (MVS) algorithm as input and improves them…
Real-Time Dense 3D Mapping of Underwater Environments
Weihan Wang, Bharat Joshi, Nathaniel Burgdorfer +4
This paper addresses real-time dense 3D reconstruction for a resource-constrained Autonomous Underwater Vehicle (AUV). Underwater vision-guided operations are among the most challe…
Learning the Distribution of Errors in Stereo Matching for Joint Disparity and Uncertainty Estimation
Liyan Chen, Weihan Wang, Philippos Mordohai
We present a new loss function for joint disparity and uncertainty estimation in deep stereo matching. Our work is motivated by the need for precise uncertainty estimates and the o…
Single-Camera 3D Head Fitting for Mixed Reality Clinical Applications
Tejas Mane, Aylar Bayramova, Kostas Daniilidis +2
We address the problem of estimating the shape of a person's head, defined as the geometry of the complete head surface, from a video taken with a single moving camera, and determi…
Do End-to-end Stereo Algorithms Under-utilize Information?
Changjiang Cai, Philippos Mordohai
Deep networks for stereo matching typically leverage 2D or 3D convolutional encoder-decoder architectures to aggregate cost and regularize the cost volume for accurate disparity es…
Matching-space Stereo Networks for Cross-domain Generalization
Changjiang Cai, Matteo Poggi, Stefano Mattoccia +1
End-to-end deep networks represent the state of the art for stereo matching. While excelling on images framing environments similar to the training set, major drops in accuracy occ…
On the Synergies between Machine Learning and Binocular Stereo for Depth Estimation from Images: a Survey
Matteo Poggi, Fabio Tosi, Konstantinos Batsos +2
Stereo matching is one of the longest-standing problems in computer vision with close to 40 years of studies and research. Throughout the years the paradigm has shifted from local,…
Oriented Point Sampling for Plane Detection in Unorganized Point Clouds
Bo Sun, Philippos Mordohai
Plane detection in 3D point clouds is a crucial pre-processing step for applications such as point cloud segmentation, semantic mapping and SLAM. In contrast to many recent plane d…
CBMV: A Coalesced Bidirectional Matching Volume for Disparity Estimation
Konstantinos Batsos, Changjiang Cai, Philippos Mordohai
Recently, there has been a paradigm shift in stereo matching with learning-based methods achieving the best results on all popular benchmarks. The success of these methods is due t…
3D Interest Point Detection via Discriminative Learning
Leizer Teran, Philippos Mordohai
The task of detecting the interest points in 3D meshes has typically been handled by geometric methods. These methods, while greatly describing human preference, can be ill-equippe…