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most citedTowards Explainable Fake Image Detection with Multi-Modal Large Language Models

2 citations · 3 across the 15 of their papers we have counts for

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cs.CV2026

Source-Face Authenticity Detection for 3D Gaussian Heads Reconstructed from a Single Portrait: A Benchmark and Dedicated Detector

Yujie Gao, Zijian Yu, Yan Hong +2

Recent advances in single-image 3D Gaussian head reconstruction have enabled highly realistic and freely renderable digital heads from a single portrait. However, reconstruction an…

cs.CV2026

VTONGuard: Automatic Detection and Authentication of AI-Generated Virtual Try-On Content

Shengyi Wu, Yan Hong, Shengyao Chen +5

With the rapid advancement of generative AI, virtual try-on (VTON) systems are becoming increasingly common in e-commerce and digital entertainment. However, the growing realism of…

cs.CV2025

Locate-Then-Examine: Grounded Region Reasoning Improves Detection of AI-Generated Images

Yikun Ji, Yan Hong, Bowen Deng +5

The rapid growth of AI-generated imagery has blurred the boundary between real and synthetic content, raising practical concerns for digital integrity. Vision-language models (VLMs…

cs.CV2025

GAMMA: Generalizable Alignment via Multi-task and Manipulation-Augmented Training for AI-Generated Image Detection

Haozhen Yan, Yan Hong, Suning Lang +6

With generative models becoming increasingly sophisticated and diverse, detecting AI-generated images has become increasingly challenging. While existing AI-genereted Image detecto…

cs.CV2025

DS-VTON: An Enhanced Dual-Scale Coarse-to-Fine Framework for Virtual Try-On

Xianbing Sun, Yan Hong, Jiahui Zhan +5

Despite recent progress, most existing virtual try-on methods still struggle to simultaneously address two core challenges: accurately aligning the garment image with the target hu…

cs.CV2025

NTIRE 2025 challenge on Text to Image Generation Model Quality Assessment

Shuhao Han, Haotian Fan, Fangyuan Kong +112

This paper reports on the NTIRE 2025 challenge on Text to Image (T2I) generation model quality assessment, which will be held in conjunction with the New Trends in Image Restoratio…

cs.CV2025★ 1 cited

Robustness in AI-Generated Detection: Enhancing Resistance to Adversarial Attacks

Sun Haoxuan, Hong Yan, Zhan Jiahui +6

The rapid advancement of generative image technology has introduced significant security concerns, particularly in the domain of face generation detection. This paper investigates…

cs.CV2025

Benchmarking Unified Face Attack Detection via Hierarchical Prompt Tuning

Ajian Liu, Haocheng Yuan, Xiao Guo +13

PAD and FFD are proposed to protect face data from physical media-based Presentation Attacks and digital editing-based DeepFakes, respectively. However, isolated training of these…

cs.CV2025★ 2 cited

Towards Explainable Fake Image Detection with Multi-Modal Large Language Models

Yikun Ji, Yan Hong, Jiahui Zhan +6

Progress in image generation raises significant public security concerns. We argue that fake image detection should not operate as a "black box". Instead, an ideal approach must en…

cs.CV2025

InterAnimate: Taming Region-aware Diffusion Model for Realistic Human Interaction Animation

Yukang Lin, Yan Hong, Zunnan Xu +10

Recent video generation research has focused heavily on isolated actions, leaving interactive motions-such as hand-face interactions-largely unexamined. These interactions are esse…

cs.CV2024

DomainGallery: Few-shot Domain-driven Image Generation by Attribute-centric Finetuning

Yuxuan Duan, Yan Hong, Bo Zhang +6

The recent progress in text-to-image models pretrained on large-scale datasets has enabled us to generate various images as long as we provide a text prompt describing what we want…

cs.CV2024

Efficient Transfer Learning for Video-language Foundation Models

Haoxing Chen, Zizheng Huang, Yan Hong +5

Pre-trained vision-language models provide a robust foundation for efficient transfer learning across various downstream tasks. In the field of video action recognition, mainstream…

cs.CV2024

Supervised Contrastive Learning for Snapshot Spectral Imaging Face Anti-Spoofing

Chuanbiao Song, Yan Hong, Jun Lan +3

This study reveals a cutting-edge re-balanced contrastive learning strategy aimed at strengthening face anti-spoofing capabilities within facial recognition systems, with a focus o…

cs.CV2024

DeMamba: AI-Generated Video Detection on Million-Scale GenVideo Benchmark

Haoxing Chen, Yan Hong, Zizheng Huang +8

Recently, video generation techniques have advanced rapidly. Given the popularity of video content on social media platforms, these models intensify concerns about the spread of fa…

cs.CV2024

Conditional Prototype Rectification Prompt Learning

Haoxing Chen, Yaohui Li, Zizheng Huang +6

Pre-trained large-scale vision-language models (VLMs) have acquired profound understanding of general visual concepts. Recent advancements in efficient transfer learning (ETL) have…

cs.CV2023

Boosting Audio-visual Zero-shot Learning with Large Language Models

Haoxing Chen, Yaohui Li, Yan Hong +6

Audio-visual zero-shot learning aims to recognize unseen classes based on paired audio-visual sequences. Recent methods mainly focus on learning multi-modal features aligned with c…