StereoPIFu: Depth Aware Clothed Human Digitization via Stereo Vision
Yang Hong, Juyong Zhang, Boyi Jiang, Yudong Guo, Ligang Liu, Hujun Bao
2021年份
21顶会引用
摘要
Ground Truth DeepHuman [60] PIFu using 2-view images [46] PIFuHD [47] Ours Figure 1. Our proposed StereoPIFu could recover high-fidelity and depth-aware reconstruction of clothed human body. Compared with state-of-the-art methods, our reconstruction is more accurate and maintains correct relative positions of different parts of the human body.
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引用它的顶会 Paper21
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它引用的顶会 Paper14
- PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human DigitizationShunsuke Saito, Zeng Huang, Ryota Natsume, Shigeo Morishima 等ICCV 2019 · 被引用 1,411 次
- Learning to Reconstruct 3D Human Pose and Shape via Model-Fitting in the LoopNikos Kolotouros, Georgios Pavlakos, Michael J. Black, Kostas DaniilidisICCV 2019 · 被引用 1,139 次
- Implicit Geometric Regularization for Learning ShapesAmos Gropp, Lior Yariv, Niv Haim, Matan Atzmon 等ICML 2020 · 被引用 1,001 次
- Multi-Garment Net: Learning to Dress 3D People From ImagesBharat Lal Bhatnagar, Garvita Tiwari, Christian Theobalt, Gerard Pons-MollICCV 2019 · 被引用 447 次
- DeepHuman: 3D Human Reconstruction From a Single ImageZerong Zheng, Tao Yu, Yixuan Wei, Qionghai Dai 等ICCV 2019 · 被引用 367 次
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