no code implementations • ECCV 2020 • Zhetong Liang, Shi Guo, Hong Gu, Huaqi Zhang, Lei Zhang
On one hand, most of the models are trained on video sequences with synthetic noise.
no code implementations • 1 Dec 2022 • Shaojia Ge, Hong Gu, Weimin Su, Anne Lönnqvist, Oleg Antropov
To overcome those limitations, here we introduce contrastive regression into EO based forest mapping and develop a novel semisupervised regression framework for wall-to-wall mapping of continuous forest variables.
no code implementations • 5 Jun 2023 • YuTing Liu, Hong Gu, Pan Qin
To this end, we propose a method to improve the verification performance for SVMs with nonlinear kernels.
no code implementations • 12 Aug 2023 • Shiyuan Piao, Hong Gu, Aina Wang, Pan Qin
To this end, we propose a domain-adaptive PINN (da-PINN) to solve inverse problems of Maxwell's equations in heterogeneous media.
no code implementations • ICCV 2023 • Zhu Yu, Zehua Sheng, Zili Zhou, Lun Luo, Si-Yuan Cao, Hong Gu, Huaqi Zhang, Hui-Liang Shen
We extract 2D feature map from images and transform the sparse depth map to point cloud to extract sparse 3D features.
no code implementations • 26 Mar 2024 • Qilin Wang, Jiangning Zhang, Chengming Xu, Weijian Cao, Ying Tai, Yue Han, Yanhao Ge, Hong Gu, Chengjie Wang, Yanwei Fu
Facial Appearance Editing (FAE) aims to modify physical attributes, such as pose, expression and lighting, of human facial images while preserving attributes like identity and background, showing great importance in photograph.
no code implementations • 27 Mar 2024 • Ruoyu Zhao, Qingnan Fan, Fei Kou, Shuai Qin, Hong Gu, Wei Wu, Pengcheng Xu, Mingrui Zhu, Nannan Wang, Xinbo Gao
Two key techniques are introduced into InstructBrush, Attention-based Instruction Optimization and Transformation-oriented Instruction Initialization, to address the limitations of the previous method in terms of inversion effects and instruction generalization.
no code implementations • 10 Apr 2024 • Yanqi Ge, Jiaqi Liu, Qingnan Fan, Xi Jiang, Ye Huang, Shuai Qin, Hong Gu, Wen Li, Lixin Duan
In this work, we propose a novel solution to the text-driven style transfer task, namely, Adaptive Style Incorporation~(ASI), to achieve fine-grained feature-level style incorporation.
no code implementations • 18 Apr 2024 • Wei Wu, Qingnan Fan, Shuai Qin, Hong Gu, Ruoyu Zhao, Antoni B. Chan
Precise image editing with text-to-image models has attracted increasing interest due to their remarkable generative capabilities and user-friendly nature.