5 citations · 6 across the 7 of their papers we have counts for
5 papers · 1 filter
Seeing Without Exposing: Adaptive Privacy Control for Open-World, Context-Hungry MLLMs
Siyuan Xu, Yibing Liu, Peilin Chen +3
Multimodal large language models (MLLMs) have raised new privacy challenges. On the data side, user-provided inputs often include unpredictable sensitive information; while on the…
When Recovery Matters: The Blind Spot of Surrogate Privacy in MLLM Editing
Siyuan Xu, Yibing Liu, Peilin Chen +3
Multimodal Large Language Models (MLLMs) enable flexible instruction-driven image editing, but privacy risks arise when user images expose diverse and user-specific private content…
Mode-as-Sequence: Translating Multimodal Motion Prediction into Unified Sequential Mode Modeling
Zikang Zhou, Haibo Hu, Xinhong Chen +5
Multimodal motion forecasting is inherently under-supervised: each training scene provides only one realized future, yet multiple plausible futures exist. This sparse supervision o…
Geometry Reinforced Efficient Attention Tuning Equipped with Normals for Robust Stereo Matching
Jiahao Li, Xinhong Chen, Zhengmin Jiang +3
Despite remarkable advances in image-driven stereo matching over the past decade, Synthetic-to-Realistic ZeroShot (Syn-to-Real) generalization remains an open challenge. This subop…
Lightweight Deep Learning for Resource-Constrained Environments: A Survey
Hou-I Liu, Marco Galindo, Hongxia Xie +4
Over the past decade, the dominance of deep learning has prevailed across various domains of artificial intelligence, including natural language processing, computer vision, and bi…