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Sungheon Park

2 accepted papers

2023

Temporal Interpolation Is All You Need for Dynamic Neural Radiance Fields

CVPR 2023highlight

Temporal interpolation often plays a crucial role to learn meaningful representations in dynamic scenes. In this paper, we propose a novel method to train spatiotemporal neural radiance fields of dynamic scenes based on temporal interpolation of feature vectors. Two feature interpolation methods are…

Cited by 59SourcePDFScholar
2020

Procrustean Regression Networks: Learning 3D Structure of Non-Rigid Objects from 2D Annotations

ECCV 2020poster

We propose a novel framework for training neural networks which is capable of learning 3D information of non-rigid objects when only 2D annotations are available as ground truths. Recently, there have been some approaches that incorporate the problem setting of non-rigid structure-from-motion (NRSfM…

Cited by 22SourcePDFScholar