2 citations · 5 across the 14 of their papers we have counts for
9 papers · 1 filter
AI-generated Images Challenge Visual Trust in High-risk Scenarios
Yi-Zhi Wang, Yichen Xiao, Linan Yue +5
Rapid advances in image generation are eroding the evidentiary value of visual content in settings where authenticity can affect public safety and personal reputation. Yet existing…
On Aligning Hierarchical Standardized Embedding for Audio-visual Generalized Zero-shot Learning
Zihan Zhang, Jie Hong, Siyuan Fan +2
Audio-visual Generalized Zero-shot Learning (AV-GZSL) is a challenging task that aims to classify both seen and unseen objects or scenes by integrating data from audio and visual m…
EpiAgent: An Agent-Centric System for Ancient Inscription Restoration
Shipeng Zhu, Ang Chen, Na Nie +3
Ancient inscriptions, as repositories of cultural memory, have suffered from centuries of environmental and human-induced degradation. Restoring their intertwined visual and textua…
MAIL++: Multi-Modal Bi-directional Agent Layer for Vision-Language Models
Kaixiang Chen, Pengfei Fang, Hui Xue
Adapting large vision-language models (VLMs) such as CLIP to downstream tasks remains challenging, as full fine-tuning is computationally prohibitive and prone to overfitting in lo…
Text-Phase Synergy Network with Dual Priors for Unsupervised Cross-Domain Image Retrieval
Jing Yang, Hui Xue, Shipeng Zhu +1
This paper studies unsupervised cross-domain image retrieval (UCDIR), which aims to retrieve images of the same category across different domains without relying on labeled data. E…
SRasP: Self-Reorientation Adversarial Style Perturbation for Cross-Domain Few-Shot Learning
Wenqian Li, Pengfei Fang, Hui Xue
Cross-Domain Few-Shot Learning (CD-FSL) aims to transfer knowledge from a seen source domain to unseen target domains, serving as a key benchmark for evaluating the robustness and…
SVasP: Self-Versatility Adversarial Style Perturbation for Cross-Domain Few-Shot Learning
Wenqian Li, Pengfei Fang, Hui Xue
Cross-Domain Few-Shot Learning (CD-FSL) aims to transfer knowledge from seen source domains to unseen target domains, which is crucial for evaluating the generalization and robustn…
Text Image Inpainting via Global Structure-Guided Diffusion Models
Shipeng Zhu, Pengfei Fang, Chenjie Zhu +3
Real-world text can be damaged by corrosion issues caused by environmental or human factors, which hinder the preservation of the complete styles of texts, e.g., texture and struct…
PEAN: A Diffusion-Based Prior-Enhanced Attention Network for Scene Text Image Super-Resolution
Zuoyan Zhao, Hui Xue, Pengfei Fang +1
Scene text image super-resolution (STISR) aims at simultaneously increasing the resolution and readability of low-resolution scene text images, thus boosting the performance of the…