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Poster
Online Adaptation for Consistent Mesh Reconstruction in the Wild
Xueting Li · Sifei Liu · Shalini De Mello · Kihwan Kim · Xiaolong Wang · Ming-Hsuan Yang · Jan Kautz

Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1294

This paper presents an algorithm to reconstruct temporally consistent 3D meshes of deformable object instances from videos in the wild. Without requiring annotations of 3D mesh, 2D keypoints, or camera pose for each video frame, we pose video-based reconstruction as a self-supervised online adaptation problem applied to any incoming test video. We first learn a category-specific 3D reconstruction model from a collection of single-view images of the same category that jointly predicts the shape, texture, and camera pose of an image. Then, at inference time, we adapt the model to a test video over time using self-supervised regularization terms that exploit temporal consistency of an object instance to enforce that all reconstructed meshes share a common texture map, a base shape, as well as parts. We demonstrate that our algorithm recovers temporally consistent and reliable 3D structures from videos of non-rigid objects including those of animals captured in the wild -- an extremely challenging task rarely addressed before.

Author Information

Xueting Li (University of California, Merced)
Sifei Liu (NVIDIA)
Shalini De Mello (NVIDIA)

Shalini De Mello is a Senior Research Scientist at NVIDIA Research since March 2013. Her research interests are in computer vision and machine learning for human-computer interaction and smart interfaces. Her work includes NVIDIA’s shipping products for hand gesture recognition, face detection, video stabilization and GPU-optimized libraries for the development for computer vision applications on mobile platforms. She received doctoral and master’s degrees in Electrical and Computer Engineering from the University of Texas at Austin in 2008 and 2004, respectively. Outside of work, she likes to cook, travel, read and hikes with her dog.

Kihwan Kim (NVIDIA)
Xiaolong Wang (UC San Diego)
Ming-Hsuan Yang (Google / UC Merced)
Jan Kautz (NVIDIA)

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