activity
20242026
most citedAdapting Vision Foundation Models for Robust Cloud Segmentation in Remote Sensing Images

1 citations · 1 across the 6 of their papers we have counts for

collaborators
Showing cs.CVShow all

8 papers · 1 filter

cs.CV2026

Harnessing CLIP and DINO: An Uncertainty-Aware Cascaded Fusion Network for Generalizable Deepfake Image Detection

Xuechao Zou, Yi Zhou, Kai Li +4

The growing realism and accessibility of manipulated and generated faces threaten the trustworthiness of digital media. To detect such forgeries, deepfake detectors based on vision…

cs.CV2026

Multi-Agent Forensic Reasoning for Generalizable Deepfake Video Detection

Xuechao Zou, Shun Zhang, Kai Li +6

The malicious use of generative artificial intelligence to create highly realistic deepfake videos raises serious ethical concerns and poses substantial challenges to AI safety. Ho…

cs.CV2026

NG-GS: NeRF-Guided 3D Gaussian Splatting Segmentation

Yi He, Tao Wang, Yi Jin +3

Recent advances in 3D Gaussian Splatting (3DGS) have enabled highly efficient and photorealistic novel view synthesis. However, segmenting objects accurately in 3DGS remains challe…

cs.CV2026

Toward Stable Semi-Supervised Remote Sensing Segmentation via Co-Guidance and Co-Fusion

Yi Zhou, Xuechao Zou, Shun Zhang +7

Semi-supervised remote sensing (RS) image semantic segmentation offers a promising solution to alleviate the burden of exhaustive annotation, yet it fundamentally struggles with ps…

cs.CV2025

Mixture of Global and Local Experts with Diffusion Transformer for Controllable Face Generation

Xuechao Zou, Shun Zhang, Xing Fu +6

Controllable face generation poses critical challenges in generative modeling due to the intricate balance required between semantic controllability and photorealism. While existin…

cs.CV2025

Dynamic Dictionary Learning for Remote Sensing Image Segmentation

Xuechao Zou, Yue Li, Shun Zhang +5

Remote sensing image segmentation faces persistent challenges in distinguishing morphologically similar categories and adapting to diverse scene variations. While existing methods…