Search Results for author: Tanner Schmidt

Found 8 papers, 3 papers with code

ERF: Explicit Radiance Field Reconstruction From Scratch

no code implementations28 Feb 2022 Samir Aroudj, Steven Lovegrove, Eddy Ilg, Tanner Schmidt, Michael Goesele, Richard Newcombe

Robustly reconstructing such a volumetric scene model with millions of unknown variables from registered scene images only is a highly non-convex and complex optimization problem.

3D Reconstruction

Identity-Disentangled Neural Deformation Model for Dynamic Meshes

no code implementations30 Sep 2021 Binbin Xu, Lingni Ma, Yuting Ye, Tanner Schmidt, Christopher D. Twigg, Steven Lovegrove

When applied to dynamically deforming shapes such as the human hands, however, they would need to preserve temporal coherence of the deformation as well as the intrinsic identity of the subject.

Disentanglement

Neural 3D Video Synthesis from Multi-view Video

1 code implementation CVPR 2022 Tianye Li, Mira Slavcheva, Michael Zollhoefer, Simon Green, Christoph Lassner, Changil Kim, Tanner Schmidt, Steven Lovegrove, Michael Goesele, Richard Newcombe, Zhaoyang Lv

We propose a novel approach for 3D video synthesis that is able to represent multi-view video recordings of a dynamic real-world scene in a compact, yet expressive representation that enables high-quality view synthesis and motion interpolation.

Motion Interpolation

STaR: Self-supervised Tracking and Reconstruction of Rigid Objects in Motion with Neural Rendering

no code implementations CVPR 2021 Wentao Yuan, Zhaoyang Lv, Tanner Schmidt, Steven Lovegrove

We achieve this by jointly optimizing the parameters of two neural radiance fields and a set of rigid poses which align the two fields at each frame.

Neural Rendering

FroDO: From Detections to 3D Objects

no code implementations11 May 2020 Kejie Li, Martin Rünz, Meng Tang, Lingni Ma, Chen Kong, Tanner Schmidt, Ian Reid, Lourdes Agapito, Julian Straub, Steven Lovegrove, Richard Newcombe

We introduce FroDO, a method for accurate 3D reconstruction of object instances from RGB video that infers object location, pose and shape in a coarse-to-fine manner.

3D Reconstruction Object Reconstruction +1

Dynamic High Resolution Deformable Articulated Tracking

no code implementations21 Nov 2017 Aaron Walsman, Weilin Wan, Tanner Schmidt, Dieter Fox

The last several years have seen significant progress in using depth cameras for tracking articulated objects such as human bodies, hands, and robotic manipulators.

Pose Estimation

PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes

10 code implementations1 Nov 2017 Yu Xiang, Tanner Schmidt, Venkatraman Narayanan, Dieter Fox

We conduct extensive experiments on our YCB-Video dataset and the OccludedLINEMOD dataset to show that PoseCNN is highly robust to occlusions, can handle symmetric objects, and provide accurate pose estimation using only color images as input.

6D Pose Estimation 6D Pose Estimation using RGB +1

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