1 code implementation • CVPR 2023 • Ju He, Jieneng Chen, Ming-Xian Lin, Qihang Yu, Alan Yuille
Compositor achieves state-of-the-art performance on PartImageNet and Pascal-Part by outperforming previous methods by around 0. 9% and 1. 3% on PartImageNet, 0. 4% and 1. 7% on Pascal-Part in terms of part and object mIoU and demonstrates better robustness against occlusion by around 4. 4% and 7. 1% on part and object respectively.
no code implementations • ICCV 2021 • Ming-Xian Lin, Jie Yang, He Wang, Yu-Kun Lai, Rongfei Jia, Binqiang Zhao, Lin Gao
Inspired by the great success in recent contrastive learning works on self-supervised representation learning, we propose a novel IBSR pipeline leveraging contrastive learning.
no code implementations • 13 Oct 2020 • Lin Gao, Tong Wu, Yu-Jie Yuan, Ming-Xian Lin, Yu-Kun Lai, Hao Zhang
We introduce a conditional autoregressive model for texture generation, which can be conditioned on both part geometry and textures already generated for other parts to achieve texture compatibility.
Graphics