Search Results for author: Tianshuo Zhang

Found 7 papers, 3 papers with code

Shackled Dancing: A Bit-Locked Diffusion Algorithm for Lossless and Controllable Image Steganography

no code implementations16 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.

Image Generation Image Steganography +1

WMamba: Wavelet-based Mamba for Face Forgery Detection

no code implementations16 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.

Face Swapping Mamba

S2TD-Face: Reconstruct a Detailed 3D Face with Controllable Texture from a Single Sketch

1 code implementation2 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.

Face Reconstruction

Safe Self-Refinement for Transformer-based Domain Adaptation

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.

Transfer Learning Unsupervised Domain Adaptation

Shuffle Augmentation of Features from Unlabeled Data for Unsupervised Domain Adaptation

no code implementations28 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.

Transfer Learning Unsupervised Domain Adaptation

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