3 papers
cs.CV2026
PortraitAes: Intent-Conditioned Structured Portrait Aesthetic Assessment
Junzhou Xie, Haozhong Xiong, Xunyun Tian +8
Portrait aesthetic assessment assigns comparable scores according to how effectively human-centered images fulfill their photographic intent. These scores support data filtering, c…
cs.CV2025
DeCLIP: Decoupled Prompting for Multi-Label Class-Incremental Learning with CLIP
Kaile Du, Zihan Ye, Junzhou Xie +7
Multi-label class-incremental learning (MLCIL) continuously expands the label space while recognizing multiple co-occurring categories, making catastrophic forgetting a central cha…
cs.CV2024
Rebalancing Multi-Label Class-Incremental Learning
Kaile Du, Yifan Zhou, Fan Lyu +5
Multi-label class-incremental learning (MLCIL) is essential for real-world multi-label applications, allowing models to learn new labels while retaining previously learned knowledg…