no code implementations • 19 Mar 2024 • Quankai Gao, Qiangeng Xu, Zhe Cao, Ben Mildenhall, Wenchao Ma, Le Chen, Danhang Tang, Ulrich Neumann
While the optimization can draw photometric reference from the input videos or be regulated by generative models, directly supervising Gaussian motions remains underexplored.
2 code implementations • 18 Nov 2023 • Di Chang, Yichun Shi, Quankai Gao, Jessica Fu, Hongyi Xu, Guoxian Song, Qing Yan, Yizhe Zhu, Xiao Yang, Mohammad Soleymani
In this work, we propose MagicPose, a diffusion-based model for 2D human pose and facial expression retargeting.
1 code implementation • 24 Sep 2023 • Cho-Ying Wu, Quankai Gao, Chin-Cheng Hsu, Te-Lin Wu, Jing-Wen Chen, Ulrich Neumann
To facilitate our investigation for robustness and address limitations of previous works, we collect InSpaceType, a high-quality and high-resolution RGBD dataset for general indoor environments.
Indoor Monocular Depth Estimation Monocular Depth Estimation
1 code implementation • ICCV 2023 • Quankai Gao, Qiangeng Xu, Hao Su, Ulrich Neumann, Zexiang Xu
In contrast to TensoRF which uses a global tensor and focuses on their vector-matrix decomposition, we propose to utilize a cloud of local tensors and apply the classic CANDECOMP/PARAFAC (CP) decomposition to factorize each tensor into triple vectors that express local feature distributions along spatial axes and compactly encode a local neural field.
1 code implementation • 30 Aug 2022 • Fariborz Taherkhani, Aashish Rai, Quankai Gao, Shaunak Srivastava, Xuanbai Chen, Fernando de la Torre, Steven Song, Aayush Prakash, Daeil Kim
3D face modeling has been an active area of research in computer vision and computer graphics, fueling applications ranging from facial expression transfer in virtual avatars to synthetic data generation.
1 code implementation • CVPR 2021 • Quankai Gao, Fudong Wang, Nan Xue, Jin-Gang Yu, Gui-Song Xia
Recently, deep learning based methods have demonstrated promising results on the graph matching problem, by relying on the descriptive capability of deep features extracted on graph nodes.
Ranked #7 on Graph Matching on Willow Object Class