collaborators

11 papers

cs.CV2026

Measured Sliders: Learning Continuous Controls from Differentiable Image Measurements

Yijia Chen, Boyu Wei, Xuanhua Yin

Continuous sliders are useful only when coefficient changes produce predictable image changes. Yet most diffusion sliders derive their axes from text or learned representations, le…

cs.CV2026

DefaultShift: Auditing Semantic Default Shift in Accelerated Text-to-Image Models

Xuanhua Yin, Chuanzhi Xu, Shunqi Mao +2

Few-step text-to-image models increasingly replace slower generators, yet acceleration can silently change distributions over unspecified attributes even when individual outputs re…

cs.CV2026

Calibrate What You SHIP: Post-Selection Risk Control for Verifier-Guided Text-to-Image Generation

Xuanhua Yin, Shunqi Mao, Wei Guo +2

Verifier-guided text-to-image systems increasingly use test-time search to select, refine, or stop among multiple candidates, yet release thresholds are often calibrated on individ…

cs.CV2026

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

Chuanzhi Xu, Ziyuan Tao, Jean Julien KNell +5

Personalized image enhancement should reflect individual aesthetic taste, yet learning such preferences commonly depends on private photos and ratings that are unsuitable for centr…

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

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…