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20202023
most citedFrom Synthetic to Real: Unsupervised Domain Adaptation for Animal Pose Estimation

8 citations · 48 across the 22 of their papers we have counts for

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30 papers · 1 filter

cs.CV2023

GeT: Generative Target Structure Debiasing for Domain Adaptation

Can Zhang, Gim Hee Lee

Domain adaptation (DA) aims to transfer knowledge from a fully labeled source to a scarcely labeled or totally unlabeled target under domain shift. Recently, semi-supervised learni…

cs.CV2023

DReg-NeRF: Deep Registration for Neural Radiance Fields

Yu Chen, Gim Hee Lee

Although Neural Radiance Fields (NeRF) is popular in the computer vision community recently, registering multiple NeRFs has yet to gain much attention. Unlike the existing work, Ne…

cs.CV2023

GHuNeRF: Generalizable Human NeRF from a Monocular Video

Chen Li, Jiahao Lin, Gim Hee Lee

In this paper, we tackle the challenging task of learning a generalizable human NeRF model from a monocular video. Although existing generalizable human NeRFs have achieved impress…

cs.CV20232 cited

NU-MCC: Multiview Compressive Coding with Neighborhood Decoder and Repulsive UDF

Stefan Lionar, Xiangyu Xu, Min Lin +1

Remarkable progress has been made in 3D reconstruction from single-view RGB-D inputs. MCC is the current state-of-the-art method in this field, which achieves unprecedented success…

cs.CV2023

OD-NeRF: Efficient Training of On-the-Fly Dynamic Neural Radiance Fields

Zhiwen Yan, Chen Li, Gim Hee Lee

Dynamic neural radiance fields (dynamic NeRFs) have demonstrated impressive results in novel view synthesis on 3D dynamic scenes. However, they often require complete video sequenc…

cs.CV2023

Boosting Long-tailed Object Detection via Step-wise Learning on Smooth-tail Data

Na Dong, Yongqiang Zhang, Mingli Ding +1

Real-world data tends to follow a long-tailed distribution, where the class imbalance results in dominance of the head classes during training. In this paper, we propose a frustrat…