no code implementations • 27 May 2024 • Anran Liu, Cheng Lin, YuAn Liu, Xiaoxiao Long, Zhiyang Dou, Hao-Xiang Guo, Ping Luo, Wenping Wang
However, all the existing methods represent the target object as a closed mesh devoid of any structural information, thus neglecting the part-based structure, which is crucial for many downstream applications, of the reconstructed shape.
no code implementations • 27 May 2024 • Yuqing Zhang, YuAn Liu, Zhiyu Xie, Lei Yang, Zhongyuan Liu, Mengzhou Yang, Runze Zhang, Qilong Kou, Cheng Lin, Wenping Wang, Xiaogang Jin
2D diffusion model, which often contains unwanted baked-in shading effects and results in unrealistic rendering effects in the downstream applications.
no code implementations • 19 May 2024 • Peng Li, YuAn Liu, Xiaoxiao Long, Feihu Zhang, Cheng Lin, Mengfei Li, Xingqun Qi, Shanghang Zhang, Wenhan Luo, Ping Tan, Wenping Wang, Qifeng Liu, Yike Guo
Specifically, these methods assume that the input images should comply with a predefined camera type, e. g. a perspective camera with a fixed focal length, leading to distorted shapes when the assumption fails.
no code implementations • 8 Feb 2024 • Xiaoxiao Long, Yuhang Zheng, Yupeng Zheng, Beiwen Tian, Cheng Lin, Lingjie Liu, Hao Zhao, Guyue Zhou, Wenping Wang
We introduce a novel approach to learn geometries such as depth and surface normal from images while incorporating geometric context.
no code implementations • 23 Jan 2024 • Zimeng Wang, Zhiyang Dou, Rui Xu, Cheng Lin, YuAn Liu, Xiaoxiao Long, Shiqing Xin, Taku Komura, Xiaoming Yuan, Wenping Wang
We introduce Coverage Axis++, a novel and efficient approach to 3D shape skeletonization.
no code implementations • 28 Nov 2023 • Zhengming Yu, Zhiyang Dou, Xiaoxiao Long, Cheng Lin, Zekun Li, YuAn Liu, Norman Müller, Taku Komura, Marc Habermann, Christian Theobalt, Xin Li, Wenping Wang
The experiments demonstrate the superior performance of Surf-D in shape generation across multiple modalities as conditions.
1 code implementation • 23 Oct 2023 • Xiaoxiao Long, Yuan-Chen Guo, Cheng Lin, YuAn Liu, Zhiyang Dou, Lingjie Liu, Yuexin Ma, Song-Hai Zhang, Marc Habermann, Christian Theobalt, Wenping Wang
In this work, we introduce Wonder3D, a novel method for efficiently generating high-fidelity textured meshes from single-view images. Recent methods based on Score Distillation Sampling (SDS) have shown the potential to recover 3D geometry from 2D diffusion priors, but they typically suffer from time-consuming per-shape optimization and inconsistent geometry.
2 code implementations • 7 Sep 2023 • YuAn Liu, Cheng Lin, Zijiao Zeng, Xiaoxiao Long, Lingjie Liu, Taku Komura, Wenping Wang
In this paper, we present a novel diffusion model called that generates multiview-consistent images from a single-view image.
1 code implementation • 27 May 2023 • YuAn Liu, Peng Wang, Cheng Lin, Xiaoxiao Long, Jiepeng Wang, Lingjie Liu, Taku Komura, Wenping Wang
We present a neural rendering-based method called NeRO for reconstructing the geometry and the BRDF of reflective objects from multiview images captured in an unknown environment.
no code implementations • CVPR 2023 • Xiaoxiao Long, Cheng Lin, Lingjie Liu, YuAn Liu, Peng Wang, Christian Theobalt, Taku Komura, Wenping Wang
In this paper, we propose to represent surfaces as the Unsigned Distance Function (UDF) and develop a new volume rendering scheme to learn the neural UDF representation.
no code implementations • ICCV 2023 • Zhiyang Dou, Qingxuan Wu, Cheng Lin, Zeyu Cao, Qiangqiang Wu, Weilin Wan, Taku Komura, Wenping Wang
We further demonstrate the generalizability of our method on hand mesh recovery.
1 code implementation • 12 Jun 2022 • Xiaoxiao Long, Cheng Lin, Peng Wang, Taku Komura, Wenping Wang
We introduce SparseNeuS, a novel neural rendering based method for the task of surface reconstruction from multi-view images.
no code implementations • 9 Jun 2022 • Cheng Lin, Adel Daoud, Maria Branden
In this paper, we build on the theory of cumulative disadvantage and examine whether the accumulated use of social assistance over the life course is associated with an increased risk of future social assistance recipiency.
no code implementations • CVPR 2022 • Weikai Chen, Cheng Lin, Weiyang Li, Bo Yang
The key to our method is the introduction of a new sign, the NULL sign, in addition to the conventional in and out labels.
1 code implementation • 22 Apr 2022 • YuAn Liu, Yilin Wen, Sida Peng, Cheng Lin, Xiaoxiao Long, Taku Komura, Wenping Wang
In this paper, we present a generalizable model-free 6-DoF object pose estimator called Gen6D.
1 code implementation • ICCV 2021 • Xiaoxiao Long, Cheng Lin, Lingjie Liu, Wei Li, Christian Theobalt, Ruigang Yang, Wenping Wang
We present a novel method for single image depth estimation using surface normal constraints.
2 code implementations • CVPR 2021 • Cheng Lin, Changjian Li, YuAn Liu, Nenglun Chen, Yi-King Choi, Wenping Wang
We introduce Point2Skeleton, an unsupervised method to learn skeletal representations from point clouds.
no code implementations • 30 Nov 2020 • Risheng Huang, Li Shen, Xuan Wang, Cheng Lin, Hao-Zhi Huang
This paper proposes an adaptive compact attention model for few-shot video-to-video translation.
no code implementations • CVPR 2021 • YuAn Liu, Lingjie Liu, Cheng Lin, Zhen Dong, Wenping Wang
We propose a novel formulation of fitting coherent motions with a smooth function on a graph of correspondences and show that this formulation allows a closed-form solution by graph Laplacian.
1 code implementation • 22 Oct 2020 • Cheng Lin, Lingjie Liu, Changjian Li, Leif Kobbelt, Bin Wang, Shiqing Xin, Wenping Wang
Segmenting arbitrary 3D objects into constituent parts that are structurally meaningful is a fundamental problem encountered in a wide range of computer graphics applications.
2 code implementations • ECCV 2020 • Cheng Lin, Tingxiang Fan, Wenping Wang, Matthias Nießner
We explore how to enable machines to model 3D shapes like human modelers using deep reinforcement learning (RL).
no code implementations • ICCV 2019 • Cheng Lin, Changjian Li, Wenping Wang
We present a novel approach to align partial 3D reconstructions which may not have substantial overlap.