57 citations · 124 across the 25 of their papers we have counts for
21 papers
TRG-Net: An Interpretable and Controllable Rain Generator
Zhiqiang Pang, Hong Wang, Qi Xie +2
Exploring and modeling rain generation mechanism is critical for augmenting paired data to ease training of rainy image processing models. Against this task, this study proposes a…
DAMSDet: Dynamic Adaptive Multispectral Detection Transformer with Competitive Query Selection and Adaptive Feature Fusion
Junjie Guo, Chenqiang Gao, Fangcen Liu +2
Infrared-visible object detection aims to achieve robust even full-day object detection by fusing the complementary information of infrared and visible images. However, highly dyna…
HIR-Diff: Unsupervised Hyperspectral Image Restoration Via Improved Diffusion Models
Li Pang, Xiangyu Rui, Long Cui +3
Hyperspectral image (HSI) restoration aims at recovering clean images from degraded observations and plays a vital role in downstream tasks. Existing model-based methods have limit…
Semi-supervised Counting via Pixel-by-pixel Density Distribution Modelling
Hui Lin, Zhiheng Ma, Rongrong Ji +4
This paper focuses on semi-supervised crowd counting, where only a small portion of the training data are labeled. We formulate the pixel-wise density value to regress as a probabi…
Quantum-Inspired Analysis of Neural Network Vulnerabilities: The Role of Conjugate Variables in System Attacks
Jun-Jie Zhang, Deyu Meng
Neural networks demonstrate inherent vulnerability to small, non-random perturbations, emerging as adversarial attacks. Such attacks, born from the gradient of the loss function re…
Gramformer: Learning Crowd Counting via Graph-Modulated Transformer
Hui Lin, Zhiheng Ma, Xiaopeng Hong +2
Transformer has been popular in recent crowd counting work since it breaks the limited receptive field of traditional CNNs. However, since crowd images always contain a large numbe…