Ying-Cong Chen
Ying-Cong Chen
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3D Vision
LucidDreamer: Towards High-Fidelity Text-to-3D Generation via Interval Score Matching
The recent advancements in text-to-3D generation mark a significant milestone in generative models, unlocking new possibilities for …
Yixun Liang
,
Xin Yang
,
Jiantao Lin
,
Haodong Li
,
Xiaogang Xu
,
Ying-Cong Chen
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Rethinking Rendering in Generalizable Neural Surface Reconstruction: A Learning-based Solution
Generalizable neural surface reconstruction techniques have attracted great attention in recent years. However, they encounter …
Yixun Liang
,
Hao He
,
Ying-Cong Chen
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Ref-NeuS: Ambiguity-Reduced Neural Implicit Surface Learning for Multi-View Reconstruction with Reflection
Neural implicit surface learning has shown significant progress in multi-view 3D reconstruction, where an object is represented by …
Wenhang Ge
,
Tao Hu
,
Haoyu Zhao
,
Shu Liu
,
Ying-Cong Chen
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Lift3D: Synthesize 3D Training Data by Lifting 2D GAN to 3D Generative Radiance Field
This work explores the use of 3D generative models to synthesize training data for 3D vision tasks. The key requirements of the …
Leheng Li
,
Qing Lian
,
Luozhou Wang
,
Ningning Ma
,
Ying-Cong Chen
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Label Name is Mantra: Unifying Point Cloud Segmentation across Heterogeneous Datasets
Point cloud segmentation is a fundamental task in 3D vision that serves a wide range of applications. Although great progresses have …
Yixun Liang
,
Hao He
,
Shishi Xiao
,
Hao Lu
,
Ying-Cong Chen
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RC-MVSNet: Unsupervised Multi-View Stereo with Neural Rendering
Finding accurate correspondences among different views is the Achilles heel of unsupervised Multi-View Stereo (MVS). Existing methods …
Di Chang
,
Aljaz Bozic
,
Tong Zhang
,
Qingsong Yan
,
Ying-Cong Chen
,
Sabine Susstrunk
,
Matthias Niebner
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Semi-supervised Monocular 3D Object Detection by Multi-view Consistency
The success of monocular 3D object detection highly relies on considerable labeled data, which is costly to obtain. To alleviate the …
Qing Lian
,
Yanbo Xu
,
Weilong Yao
,
Ying-Cong Chen
,
Tong Zhang
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