4 citations · 9 across the 14 of their papers we have counts for
15 papers
GenVideoLens: Where LVLMs Fall Short in AI-Generated Video Detection?
Yueying Zou, Pei Pei Li, Zekun Li +4
In recent years, AI-generated videos have become increasingly realistic and sophisticated. Meanwhile, Large Vision-Language Models (LVLMs) have shown strong potential for detecting…
3-Tracer: A Tri-level Temporal-Aware Framework for Audio Forgery Detection and Localization
Shuhan Xia, Xuannan Liu, Xing Cui +1
Recently, partial audio forgery has emerged as a new form of audio manipulation. Attackers selectively modify partial but semantically critical frames while preserving the overall…
SpineBench: Benchmarking Multimodal LLMs for Spinal Pathology Analysis
Chenghanyu Zhang, Zekun Li, Peipei Li +5
With the increasing integration of Multimodal Large Language Models (MLLMs) into the medical field, comprehensive evaluation of their performance in various medical domains becomes…
T^2Agent A Tool-augmented Multimodal Misinformation Detection Agent with Monte Carlo Tree Search
Xing Cui, Yueying Zou, Zekun Li +4
Real-world multimodal misinformation often arises from mixed forgery sources, requiring dynamic reasoning and adaptive verification. However, existing methods mainly rely on static…
Video-SafetyBench: A Benchmark for Safety Evaluation of Video LVLMs
Xuannan Liu, Zekun Li, Zheqi He +6
The increasing deployment of Large Vision-Language Models (LVLMs) raises safety concerns under potential malicious inputs. However, existing multimodal safety evaluations primarily…
ID-Cloak: Crafting Identity-Specific Cloaks Against Personalized Text-to-Image Generation
Qianrui Teng, Xing Cui, Xuannan Liu +4
Personalized text-to-image models allow users to generate images of new concepts from several reference photos, thereby leading to critical concerns regarding civil privacy. Althou…
Survey on AI-Generated Media Detection: From Non-MLLM to MLLM
Yueying Zou, Peipei Li, Zekun Li +5
The proliferation of AI-generated media poses significant challenges to information authenticity and social trust, making reliable detection methods highly demanded. Methods for de…
Jailbreak Attacks and Defenses against Multimodal Generative Models: A Survey
Xuannan Liu, Xing Cui, Peipei Li +6
The rapid evolution of multimodal foundation models has led to significant advancements in cross-modal understanding and generation across diverse modalities, including text, image…
MMFakeBench: A Mixed-Source Multimodal Misinformation Detection Benchmark for LVLMs
Xuannan Liu, Zekun Li, Peipei Li +6
Current multimodal misinformation detection (MMD) methods often assume a single source and type of forgery for each sample, which is insufficient for real-world scenarios where mul…
Localize, Understand, Collaborate: Semantic-Aware Dragging via Intention Reasoner
Xing Cui, Peipei Li, Zekun Li +3
Flexible and accurate drag-based editing is a challenging task that has recently garnered significant attention. Current methods typically model this problem as automatically learn…
FKA-Owl: Advancing Multimodal Fake News Detection through Knowledge-Augmented LVLMs
Xuannan Liu, Peipei Li, Huaibo Huang +6
The massive generation of multimodal fake news involving both text and images exhibits substantial distribution discrepancies, prompting the need for generalized detectors. However…
Exploring 3D-aware Lifespan Face Aging via Disentangled Shape-Texture Representations
Qianrui Teng, Rui Wang, Xing Cui +2
Existing face aging methods often focus on modeling either texture aging or using an entangled shape-texture representation to achieve face aging. However, shape and texture are tw…
InstaStyle: Inversion Noise of a Stylized Image is Secretly a Style Adviser
Xing Cui, Zekun Li, Pei Pei Li +3
Stylized text-to-image generation focuses on creating images from textual descriptions while adhering to a style specified by a few reference images. However, subtle style variatio…
Bidirectional Knowledge Reconfiguration for Lightweight Point Cloud Analysis
Peipei Li, Xing Cui, Yibo Hu +3
Point cloud analysis faces computational system overhead, limiting its application on mobile or edge devices. Directly employing small models may result in a significant drop in pe…
CHATEDIT: Towards Multi-turn Interactive Facial Image Editing via Dialogue
Xing Cui, Zekun Li, Peipei Li +3
This paper explores interactive facial image editing via dialogue and introduces the ChatEdit benchmark dataset for evaluating image editing and conversation abilities in this cont…