activity
20202025
most citedGlobal Structure-Aware Diffusion Process for Low-Light Image Enhancement

43 citations · 117 across the 9 of their papers we have counts for

collaborators

14 papers

cs.LG2025

Mitigating Sample-Level Imbalance via Probabilistic Separation for Adaptive Multimodal Fusion

Zhiwen Yu, Zhaocheng Liu, Xiaoqing Liu +2

Multimodal learning faces modality imbalance, where dominant modalities suppress weaker ones due to inconsistent convergence rates. Existing static or heuristic methods overlook sa…

cs.CV2025

Exploring Non-Local Spatial-Angular Correlations with a Hybrid Mamba-Transformer Framework for Light Field Super-Resolution

Haosong Liu, Xiancheng Zhu, Huanqiang Zeng +3

Recently, Mamba-based methods, with its advantage in long-range information modeling and linear complexity, have shown great potential in optimizing both computational cost and per…

eess.IV2025

FD-LSCIC: Frequency Decomposition-based Learned Screen Content Image Compression

Shiqi Jiang, Hui Yuan, Shuai Li +2

The learned image compression (LIC) methods have already surpassed traditional techniques in compressing natural scene (NS) images. However, directly applying these methods to scre…

cs.CV2024

Unsupervised 3D Point Cloud Completion via Multi-view Adversarial Learning

Lintai Wu, Xianjing Cheng, Yong Xu +2

In real-world scenarios, scanned point clouds are often incomplete due to occlusion issues. The tasks of self-supervised and weakly-supervised point cloud completion involve recons…

cs.CV2023★ 43 cited

Global Structure-Aware Diffusion Process for Low-Light Image Enhancement

Jinhui Hou, Zhiyu Zhu, Junhui Hou +3

This paper studies a diffusion-based framework to address the low-light image enhancement problem. To harness the capabilities of diffusion models, we delve into this intricate pro…

cs.CV2023★ 2 cited

Deep Diversity-Enhanced Feature Representation of Hyperspectral Images

Jinhui Hou, Zhiyu Zhu, Junhui Hou +3

In this paper, we study the problem of efficiently and effectively embedding the high-dimensional spatio-spectral information of hyperspectral (HS) images, guided by feature divers…