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20242026
most citedAnySynth: Harnessing the Power of Image Synthetic Data Generation for Generalized Vision-Language Tasks

1 citations · 3 across the 8 of their papers we have counts for

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cs.CV2026

Echoes of ownership: Adversarial-guided dual injection for copyright protection in MLLMs

Chengwei Xia, Fan Ma, Ruijie Quan +3

With the rapid deployment of multimodal large language models (MLLMs), disputes regarding model ownership have become increasingly frequent, raising significant concerns about inte…

cs.CV2025

ContextGen: Contextual Layout Anchoring for Identity-Consistent Multi-Instance Generation

Ruihang Xu, Dewei Zhou, Fan Ma +1

Multi-instance image generation (MIG) remains a significant challenge for modern diffusion models due to key limitations in achieving precise control over object layout and preserv…

cs.CV2025

Adversarial-Guided Diffusion for Multimodal LLM Attacks

Chengwei Xia, Fan Ma, Ruijie Quan +2

This paper addresses the challenge of generating adversarial image using a diffusion model to deceive multimodal large language models (MLLMs) into generating the targeted response…

cs.CV20251 cited

BrainGuard: Privacy-Preserving Multisubject Image Reconstructions from Brain Activities

Zhibo Tian, Ruijie Quan, Fan Ma +2

Reconstructing perceived images from human brain activity forms a crucial link between human and machine learning through Brain-Computer Interfaces. Early methods primarily focused…

cs.CV20241 cited

Imagine and Seek: Improving Composed Image Retrieval with an Imagined Proxy

You Li, Fan Ma, Yi Yang

The Zero-shot Composed Image Retrieval (ZSCIR) requires retrieving images that match the query image and the relative captions. Current methods focus on projecting the query image…

cs.CV20241 cited

AnySynth: Harnessing the Power of Image Synthetic Data Generation for Generalized Vision-Language Tasks

You Li, Fan Ma, Yi Yang

Diffusion models have recently been employed to generate high-quality images, reducing the need for manual data collection and improving model generalization in tasks such as objec…