1 citations · 1 across the 4 of their papers we have counts for
6 papers
UrbanMoE: A Sparse Multi-Modal Mixture-of-Experts Framework for Multi-Task Urban Region Profiling
Pingping Liu, Jiamiao Liu, Zijian Zhang +5
Urban region profiling, the task of characterizing geographical areas, is crucial for urban planning and resource allocation. However, existing research in this domain faces two si…
SPJFNet: Self-Mining Prior-Guided Joint Frequency Enhancement for Ultra-Efficient Dark Image Restoration
Tongshun Zhang, Pingling Liu, Zijian Zhang +1
Current dark image restoration methods suffer from severe efficiency bottlenecks, primarily stemming from: (1) computational burden and error correction costs associated with relia…
CIVQLLIE: Causal Intervention with Vector Quantization for Low-Light Image Enhancement
Tongshun Zhang, Pingping Liu, Zhe Zhang +1
Images captured in nighttime scenes suffer from severely reduced visibility, hindering effective content perception. Current low-light image enhancement (LLIE) methods face signifi…
Beyond Illumination: Fine-Grained Detail Preservation in Extreme Dark Image Restoration
Tongshun Zhang, Pingping Liu, Zixuan Zhong +2
Recovering fine-grained details in extremely dark images remains challenging due to severe structural information loss and noise corruption. Existing enhancement methods often fail…
CWNet: Causal Wavelet Network for Low-Light Image Enhancement
Tongshun Zhang, Pingping Liu, Yubing Lu +4
Traditional Low-Light Image Enhancement (LLIE) methods primarily focus on uniform brightness adjustment, often neglecting instance-level semantic information and the inherent chara…
BSMamba: Brightness and Semantic Modeling for Long-Range Interaction in Low-Light Image Enhancement
Tongshun Zhang, Pingping Liu, Mengen Cai +3
Current low-light image enhancement (LLIE) methods face significant limitations in simultaneously improving brightness while preserving semantic consistency, fine details, and comp…