no code implementations • 16 May 2025 • Tianshuo Zhang, Gao Jia, Wenzhe Zhai, Rui Yann, Xianglei Xing
Data steganography aims to conceal information within visual content, yet existing spatial- and frequency-domain approaches suffer from trade-offs between security, capacity, and perceptual quality.
no code implementations • 4 May 2025 • Siran Peng, Zipei Wang, Li Gao, Xiangyu Zhu, Tianshuo Zhang, Ajian Liu, Haoyuan Zhang, Zhen Lei
In this paper, we propose VLF-FFD, a novel Vision-Language Fusion solution for MLLM-enhanced Face Forgery Detection.
no code implementations • 16 Jan 2025 • Siran Peng, Tianshuo Zhang, Li Gao, Xiangyu Zhu, Haoyuan Zhang, Kai Pang, Zhen Lei
Extensive experimental results show that WMamba achieves state-of-the-art (SOTA) performance, highlighting its effectiveness and superiority in face forgery detection.
1 code implementation • 2 Aug 2024 • Zidu Wang, Xiangyu Zhu, Jiang Yu, Tianshuo Zhang, Zhen Lei
Furthermore, S2TD-Face introduces a texture control module utilizing text prompts to select the most suitable textures from a library and seamlessly integrate them into the geometry, resulting in a 3D detailed face with controllable texture.
2 code implementations • CVPR 2024 • Zidu Wang, Xiangyu Zhu, Tianshuo Zhang, Baiqin Wang, Zhen Lei
In this paper, we fully utilize the facial part segmentation geometry by introducing Part Re-projection Distance Loss (PRDL).
Ranked #3 on
3D Face Reconstruction
on REALY (side-view)
1 code implementation • CVPR 2022 • Tao Sun, Cheng Lu, Tianshuo Zhang, Haibin Ling
Unsupervised Domain Adaptation (UDA) aims to leverage a label-rich source domain to solve tasks on a related unlabeled target domain.
Ranked #4 on
Domain Adaptation
on Office-31
no code implementations • 28 Jan 2022 • Changwei Xu, Jianfei Yang, Haoran Tang, Han Zou, Cheng Lu, Tianshuo Zhang
Unsupervised Domain Adaptation (UDA), a branch of transfer learning where labels for target samples are unavailable, has been widely researched and developed in recent years with the help of adversarially trained models.