activity
20212026
most citedA Deep Learning based No-reference Quality Assessment Model for UGC Videos

240 citations · 805 across the 94 of their papers we have counts for

collaborators

95 papers

cs.AI2026

SafeAtlas-VL: Beyond Binary Multimodal Safety with Large-Scale Data and Guard Models

Zongrui Wang, Xiangyang Zhu, Sicheng Wang +13

Multimodal safety moderation requires distinguishing risks arising from visual content, user intent, and assistant behavior. Existing safeguards, however, are typically trained for…

cs.CV2026

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…

cs.CV2026

ICME 2026 Grand Challenge on Cross-Scenario Defect Detection and Fine-Grained Severity Grading for High-Precision Manufacturing

Wei Sun, Weixia Zhang, Linhan Cao +30

This paper presents the IEEE International Conference on Multimedia and Expo (ICME) 2026 Grand Challenge on Cross-Scenario Defect Detection and Fine-Grained Severity Grading for Hi…

cs.CV2026

DroneIQA-VLE: Multi-Task Drone Image Quality Assessment via Vision-Language Ensemble

Wei Sun, Weixia Zhang, Hongjian Zhan +3

We present DroneIQA-VLE, our solution to the ICME 2026 Drone-IQA Grand Challenge on Target-aware Image Quality Assessment for Low-altitude UAV Images. The framework jointly predict…

cs.CV2026

LEIQ-Assessor: Multi-dimensional Quality Assessment of Low-light Enhanced Images via Multi-task Learning

Wei Sun, Yanwei Jiang, Dandan Zhu +4

Low-light image enhancement algorithms (LIEAs) aim to improve the visibility of images captured under poor illumination. However, the enhancement process often introduces artifacts…

cs.LG2026

SafeSci: Safety Evaluation of Large Language Models in Science Domains and Beyond

Xiangyang Zhu, Yuan Tian, Qi Jia +14

The success of large language models (LLMs) in scientific domains has heightened safety concerns, prompting numerous benchmarks to evaluate their scientific safety. Existing benchm…

cs.CV2026

AMIF: Authorizable Medical Image Fusion Model with Built-in Authentication

Jie Song, Jun Jia, Wei Sun +3

Multimodal image fusion enables precise lesion localization and characterization for accurate diagnosis, thereby strengthening clinical decision-making and driving its growing prom…

cs.CV2026

DP^2-VL: Private Photo Dataset Protection by Data Poisoning for Vision-Language Models

Hongyi Miao, Jun Jia, Xincheng Wang +7

Recent advances in visual-language alignment have endowed vision-language models (VLMs) with fine-grained image understanding capabilities. However, this progress also introduces n…

cs.AI2026

LifeEval: A Multimodal Benchmark for Assistive AI in Egocentric Daily Life Tasks

Hengjian Gao, Kaiwei Zhang, Shibo Wang +8

The rapid progress of Multimodal Large Language Models (MLLMs) marks a significant step toward artificial general intelligence, offering great potential for augmenting human capabi…

eess.IV2026★ 1 cited

Surveillance Facial Image Quality Assessment: A Multi-dimensional Dataset and Lightweight Model

Yanwei Jiang, Wei Sun, Yingjie Zhou +8

Surveillance facial images are often captured under unconstrained conditions, resulting in severe quality degradation due to factors such as low resolution, motion blur, occlusion,…

cs.CV2026

EEmo-Logic: A Unified Dataset and Multi-Stage Framework for Comprehensive Image-Evoked Emotion Assessment

Lancheng Gao, Ziheng Jia, Zixuan Xing +4

Understanding the multi-dimensional attributes and intensity nuances of image-evoked emotions is pivotal for advancing machine empathy and empowering diverse human-computer interac…

cs.CL2026

Automated Safety Benchmarking: A Multi-agent Pipeline for LVLMs

Xiangyang Zhu, Yuan Tian, Zicheng Zhang +6

Large vision-language models (LVLMs) exhibit remarkable capabilities in cross-modal tasks but face significant safety challenges, which undermine their reliability in real-world ap…

cs.CV2026

QualiRAG: Retrieval-Augmented Generation for Visual Quality Understanding

Linhan Cao, Wei Sun, Weixia Zhang +6

Visual quality assessment (VQA) is increasingly shifting from scalar score prediction toward interpretable quality understanding -- a paradigm that demands \textit{fine-grained spa…

cs.CV2025

Adapter Shield: A Unified Framework with Built-in Authentication for Preventing Unauthorized Zero-Shot Image-to-Image Generation

Jun Jia, Hongyi Miao, Yingjie Zhou +8

With the rapid progress in diffusion models, image synthesis has advanced to the stage of zero-shot image-to-image generation, where high-fidelity replication of facial identities…

eess.IV2025

DLADiff: A Dual-Layer Defense Framework against Fine-Tuning and Zero-Shot Customization of Diffusion Models

Jun Jia, Hongyi Miao, Yingjie Zhou +8

With the rapid advancement of diffusion models, a variety of fine-tuning methods have been developed, enabling high-fidelity image generation with high similarity to the target con…

cs.CV2025

Evaluating Dataset Watermarking for Fine-tuning Traceability of Customized Diffusion Models: A Comprehensive Benchmark and Removal Approach

Xincheng Wang, Hanchi Sun, Wenjun Sun +8

Recent fine-tuning techniques for diffusion models enable them to reproduce specific image sets, such as particular faces or artistic styles, but also introduce copyright and secur…

cs.CV2025

Exploring Instruction Data Quality for Explainable Image Quality Assessment

Yunhao Li, Sijing Wu, Jun Jia +5

In recent years, with the rapid development of large multimodal models (LMMs), explainable image quality assessment (IQA) has attracted increasing attention, aiming to understand t…

cs.MM2025

XGC-AVis: Towards Audio-Visual Content Understanding with a Multi-Agent Collaborative System

Yuqin Cao, Xiongkuo Min, Yixuan Gao +4

In this paper, we propose XGC-AVis, a multi-agent framework that enhances the audio-video temporal alignment capabilities of multimodal large models (MLLMs) and improves the effici…

cs.CV2025

VQualA 2025 Challenge on Face Image Quality Assessment: Methods and Results

Sizhuo Ma, Wei-Ting Chen, Qiang Gao +56

Face images play a crucial role in numerous applications; however, real-world conditions frequently introduce degradations such as noise, blur, and compression artifacts, affecting…

cs.CL2025

SafetyFlow: An Agent-Flow System for Automated LLM Safety Benchmarking

Xiangyang Zhu, Yuan Tian, Chunyi Li +3

The rapid proliferation of large language models (LLMs) has intensified the requirement for reliable safety evaluation to uncover model vulnerabilities. To this end, numerous LLM s…

cs.CL2025

Sycophancy under Pressure: Evaluating and Mitigating Sycophantic Bias via Adversarial Dialogues in Scientific QA

Kaiwei Zhang, Qi Jia, Zijian Chen +5

Large language models (LLMs), while increasingly used in domains requiring factual rigor, often display a troubling behavior: sycophancy, the tendency to align with user beliefs re…

cs.CV2025★ 1 cited

Engagement Prediction of Short Videos with Large Multimodal Models

Wei Sun, Linhan Cao, Yuqin Cao +7

The rapid proliferation of user-generated content (UGC) on short-form video platforms has made video engagement prediction increasingly important for optimizing recommendation syst…

cs.CV2025

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation

Wei Sun, Weixia Zhang, Linhan Cao +5

Face image quality assessment (FIQA) is essential for various face-related applications. Although FIQA has been extensively studied and achieved significant progress, the computati…

cs.CV2025

Audio-Assisted Face Video Restoration with Temporal and Identity Complementary Learning

Yuqin Cao, Yixuan Gao, Wei Sun +3

Face videos accompanied by audio have become integral to our daily lives, while they often suffer from complex degradations. Most face video restoration methods neglect the intrins…