Search Results for author: Lingni Ma

Found 12 papers, 2 papers with code

In-Hand 3D Object Scanning from an RGB Sequence

no code implementations28 Nov 2022 Shreyas Hampali, Tomas Hodan, Luan Tran, Lingni Ma, Cem Keskin, Vincent Lepetit

As global optimization over all the shape and pose parameters is prone to fail without coarse-level initialization of the poses, we propose an incremental approach which starts by splitting the sequence into carefully selected overlapping segments within which the optimization is likely to succeed.

Neural Correspondence Field for Object Pose Estimation

no code implementations30 Jul 2022 Lin Huang, Tomas Hodan, Lingni Ma, Linguang Zhang, Luan Tran, Christopher Twigg, Po-Chen Wu, Junsong Yuan, Cem Keskin, Robert Wang

Unlike classical correspondence-based methods which predict 3D object coordinates at pixels of the input image, the proposed method predicts 3D object coordinates at 3D query points sampled in the camera frustum.

3D Reconstruction Pose Estimation

Snipper: A Spatiotemporal Transformer for Simultaneous Multi-Person 3D Pose Estimation Tracking and Forecasting on a Video Snippet

1 code implementation9 Jul 2022 Shihao Zou, Yuanlu Xu, Chao Li, Lingni Ma, Li Cheng, Minh Vo

In this paper, we propose Snipper, a framework to perform multi-person 3D pose estimation, tracking and motion forecasting simultaneously in a single inference.

3D Pose Estimation Motion Forecasting

Self-supervised Neural Articulated Shape and Appearance Models

no code implementations CVPR 2022 Fangyin Wei, Rohan Chabra, Lingni Ma, Christoph Lassner, Michael Zollhöfer, Szymon Rusinkiewicz, Chris Sweeney, Richard Newcombe, Mira Slavcheva

In addition, our representation enables a large variety of applications, such as few-shot reconstruction, the generation of novel articulations, and novel view-synthesis.

Novel View Synthesis

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.


Egocentric Activity Recognition and Localization on a 3D Map

no code implementations20 May 2021 Miao Liu, Lingni Ma, Kiran Somasundaram, Yin Li, Kristen Grauman, James M. Rehg, Chao Li

Given a video captured from a first person perspective and the environment context of where the video is recorded, can we recognize what the person is doing and identify where the action occurs in the 3D space?

Action Localization Action Recognition +2

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

Detailed Dense Inference with Convolutional Neural Networks via Discrete Wavelet Transform

no code implementations6 Aug 2018 Lingni Ma, Jörg Stückler, Tao Wu, Daniel Cremers

Dense pixelwise prediction such as semantic segmentation is an up-to-date challenge for deep convolutional neural networks (CNNs).

Semantic Segmentation

Multi-View Deep Learning for Consistent Semantic Mapping with RGB-D Cameras

no code implementations26 Mar 2017 Lingni Ma, Jörg Stückler, Christian Kerl, Daniel Cremers

At test time, the semantics predictions of our network can be fused more consistently in semantic keyframe maps than predictions of a network trained on individual views.

Scene Understanding Semantic Segmentation

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