Efficient reflectance capture using an autoencoder. K Kang, Z Chen, J Wang, K Zhou, H Wu ACM Trans. Graph. 37 (4), 127, 2018 | 60 | 2018 |
Learning efficient illumination multiplexing for joint capture of reflectance and shape. K Kang, C Xie, C He, M Yi, M Gu, Z Chen, K Zhou, H Wu ACM Trans. Graph. 38 (6), 165:1-165:12, 2019 | 43 | 2019 |
Free-form scanning of non-planar appearance with neural trace photography X Ma, K Kang, R Zhu, H Wu, K Zhou ACM Transactions on Graphics (TOG) 40 (4), 1-13, 2021 | 21 | 2021 |
Neural Reflectance Capture in the View-Illumination Domain K Kang, M Gu, C Xie, X Yang, H Wu, K Zhou IEEE Transactions on Visualization and Computer Graphics 29 (2), 1450-1462, 2021 | 3 | 2021 |
Learning Efficient Photometric Feature Transform for Multi-view Stereo K Kang, C Xie, R Zhu, X Ma, P Tan, H Wu, K Zhou Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 3 | 2021 |
Methods for obtaining normal vector, geometry and material of three-dimensional objects based on neural network H Wu, K Zhou, K Kaizhang US Patent 11,748,618, 2023 | 1 | 2023 |
Differentiable Dynamic Visible-Light Tomography K Kang, Z Bi, X Feng, Y Dong, K Zhou, H Wu SIGGRAPH Asia 2023 Conference Papers, 1-12, 2023 | | 2023 |
Learning Photometric Feature Transform for Free-form Object Scan X Feng, K Kang, F Pei, H Ding, J You, P Tan, K Zhou, H Wu arXiv preprint arXiv:2308.03492, 2023 | | 2023 |
DiFT: Differentiable Differential Feature Transform for Multi-View Stereo K Kang, C Zeng, H Wu, K Zhou arXiv preprint arXiv:2203.08435, 2022 | | 2022 |
Learning optimal lighting patterns for efficient SVBRDF acquisition K Kang, Z Chen, J Wang, K Zhou, H Wu ACM SIGGRAPH 2018 Posters, 1-2, 2018 | | 2018 |