23 citations · 35 across the 32 of their papers we have counts for
32 papers · 1 filter
Learning Continuous Source Responses For Generalizable AI-Generated Image Detection
Manni Cui, Ruiqi Liu, Zijian Yu +8
Advances in image generation have made synthetic images increasingly difficult to distinguish from real photographs, raising concerns about the trustworthiness of visual media. Exi…
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…
GAP-SAM: A Global Artifact Prior for Generalizable AI-Generated Image Manipulation Localization
Haozhen Yan, Siyuan Shan, Zijian Yu +4
AI-generated image manipulation localization identifies edited pixels, but its OOD performance lags behind image-level detection partly because pixel supervision entangles forensic…
Enhancing Localized Reasoning for Long Video Understanding via Efficient Segment-to-Video Supervision
Beibei Zhang, Chao Xu, Jun Lan +4
Though Multimodal Large Language Models (MLLMs) have shown impressive potential in video understanding, long video understanding (LVU) remains challenging since distracting noise i…
ArmorOCR: Grounded Adversarial Visual Perception via Observation-Transferred Self-Distillation
Linhan Cao, Siyuan Li, Jun Lan +8
Large multimodal models (LMMs) have demonstrated strong OCR recognition capabilities, yet remain vulnerable to adversarial visual text that is readable to humans but challenging fo…
Adaptive and Balanced Re-initialization for Long-timescale Continual Test-time Domain Adaptation
Yanshuo Wang, Jinguang Tong, Jun Lan +5
Continual test-time domain adaptation (CTTA) aims to adjust models so that they can perform well over time across non-stationary environments. While previous methods have made cons…
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…
Generalizable and Adaptive Continual Learning Framework for AI-generated Image Detection
Hanyi Wang, Jun Lan, Yaoyu Kang +4
The malicious misuse and widespread dissemination of AI-generated images pose a significant threat to the authenticity of online information. Current detection methods often strugg…
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…
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…
EMIT: Enhancing MLLMs for Industrial Anomaly Detection via Difficulty-Aware GRPO
Wei Guan, Jun Lan, Jian Cao +3
Industrial anomaly detection (IAD) plays a crucial role in maintaining the safety and reliability of manufacturing systems. While multimodal large language models (MLLMs) show stro…
Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs
Yikun Ji, Hong Yan, Jun Lan +5
The rapid advancement of image generation technologies intensifies the demand for interpretable and robust detection methods. Although existing approaches often attain high accurac…
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…
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…
COCO-Inpaint: A Benchmark for Detecting and Localizing Inpainting-Based Image Manipulations
Haozhen Yan, Yan Hong, Jiahui Zhan +5
Recent advances in image manipulation have enabled highly photorealistic content generation, but also lowered the barrier to arbitrary editing, raising concerns about multimedia au…
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…
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…
Maintain Plasticity in Long-timescale Continual Test-time Adaptation
Yanshuo Wang, Xuesong Li, Jinguang Tong +5
Continual test-time domain adaptation (CTTA) aims to adjust pre-trained source models to perform well over time across non-stationary target environments. While previous methods ha…
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…
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…
Stochastic Layer-Wise Shuffle for Improving Vision Mamba Training
Zizheng Huang, Haoxing Chen, Jiaqi Li +4
Recent Vision Mamba (Vim) models exhibit nearly linear complexity in sequence length, making them highly attractive for processing visual data. However, the training methodologies…
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…
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…
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…