5 papers · 1 filter
When Privacy Meets Recovery: The Overlooked Half of Surrogate-Driven Privacy Preservation for MLLM Editing
Siyuan Xu, Yibing Liu, Peilin Chen +3
Privacy leakage in Multimodal Large Language Models (MLLMs) has long been an intractable problem. Existing studies, though effectively obscure private information in MLLMs, often o…
VQualA 2025 Challenge on Visual Quality Comparison for Large Multimodal Models: Methods and Results
Hanwei Zhu, Haoning Wu, Zicheng Zhang +26
This paper presents a summary of the VQualA 2025 Challenge on Visual Quality Comparison for Large Multimodal Models (LMMs), hosted as part of the ICCV 2025 Workshop on Visual Quali…
Leveraging Diffusion Knowledge for Generative Image Compression with Fractal Frequency-Aware Band Learning
Lingyu Zhu, Xiangrui Zeng, Bolin Chen +3
By optimizing the rate-distortion-realism trade-off, generative image compression approaches produce detailed, realistic images instead of the only sharp-looking reconstructions pr…
An Information-Theoretic Regularizer for Lossy Neural Image Compression
Yingwen Zhang, Meng Wang, Xihua Sheng +4
Lossy image compression networks aim to minimize the latent entropy of images while adhering to specific distortion constraints. However, optimizing the neural network can be chall…
RCNet: Deep Recurrent Collaborative Network for Multi-View Low-Light Image Enhancement
Hao Luo, Baoliang Chen, Lingyu Zhu +2
Scene observation from multiple perspectives would bring a more comprehensive visual experience. However, in the context of acquiring multiple views in the dark, the highly correla…