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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

Shalini De Mello is a Principal Research Scientist and Research Lead in the Learning and Perception Research group at NVIDIA, which she joined in 2013. Her research interests are in human-centric vision (face and gaze analysis) and in data-efficient (synth2real, low-shot, self-supervised and multimodal) machine learning. She has co-authored 48 peer-reviewed publications and holds 38 patents. Her inventions have contributed to several NVIDIA products, including DriveIX and Maxine. Previously, she has worked at Texas Instruments and AT&T Laboratories. She received her Doctoral degree in Electrical and Computer Engineering from the University of Texas at Austin.

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

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