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From the 1 of 8 linked papers with an AI index.

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8 papers

cs.CV2026

Learning Color Grading, No Photo Sharing: Federated Aesthetic Preference Learning for Personalized Image Enhancement

Chuanzhi Xu, Ziyuan Tao, Jean Julien KNell +5

The paper proposes FedPAIE, a federated learning framework that learns individual aesthetic preferences for color grading and applies lightweight, personalized image enhancement on…

cs.CV2026

SAFE-DiT: Semantics-Aware Fast-path Execution for High-Resolution Diffusion Transformers

Xuanhua Yin, Yuxuan Jia, Chuanzhi Xu +1

High-resolution Diffusion Transformer (DiT) inference contains substantial spatial redundancy, but many spatially adaptive implementations encode regional computation as attention…

cs.CV2026

AccelAes: Accelerating Diffusion Transformers for Training-Free Aesthetic-Enhanced Image Generation

Xuanhua Yin, Chuanzhi Xu, Haoxian Zhou +2

Diffusion Transformers (DiTs) are a dominant backbone for high-fidelity text-to-image generation due to strong scalability and alignment at high resolutions. However, quadratic sel…

cs.CV2026

Aes3D: Aesthetic Assessment in 3D Gaussian Splatting

Chuanzhi Xu, Boyu Wei, Haoxian Zhou +5

As 3D Gaussian Splatting (3DGS) gains attention in immersive media and digital content creation, assessing the aesthetics of 3D scenes becomes important in helping creators build m…

q-bio.NC2026

BrainVista: Modeling Naturalistic Brain Dynamics as Multimodal Next-Token Prediction

Xuanhua Yin, Runkai Zhao, Lina Yao +1

Naturalistic fMRI characterizes the brain as a dynamic predictive engine driven by continuous sensory streams. However, modeling the causal forward evolution in realistic neural si…

cs.AI2026

Improving Multimodal Brain Encoding Model with Dynamic Subject-awareness Routing

Xuanhua Yin, Runkai Zhao, Weidong Cai

Naturalistic fMRI encoding must handle multimodal inputs, shifting fusion styles, and pronounced inter-subject variability. We introduce AFIRE (Agnostic Framework for Multimodal fM…