activity
20222024
most citedMagic ELF: Image Deraining Meets Association Learning and Transformer

6 citations · 12 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CV2024

LithoHoD: A Litho Simulator-Powered Framework for IC Layout Hotspot Detection

Hao-Chiang Shao, Guan-Yu Chen, Yu-Hsien Lin +4

Recent advances in VLSI fabrication technology have led to die shrinkage and increased layout density, creating an urgent demand for advanced hotspot detection techniques. However,…

cs.CV2024

Make Graph-based Referring Expression Comprehension Great Again through Expression-guided Dynamic Gating and Regression

Jingcheng Ke, Dele Wang, Jun-Cheng Chen +3

One common belief is that with complex models and pre-training on large-scale datasets, transformer-based methods for referring expression comprehension (REC) perform much better t…

eess.IV20241 cited

Heterogeneous window transformer for image denoising

Chunwei Tian, Menghua Zheng, Chia-Wen Lin +2

Deep networks can usually depend on extracting more structural information to improve denoising results. However, they may ignore correlation between pixels from an image to pursue…

cs.CV2024

Domain-adaptive Video Deblurring via Test-time Blurring

Jin-Ting He, Fu-Jen Tsai, Jia-Hao Wu +4

Dynamic scene video deblurring aims to remove undesirable blurry artifacts captured during the exposure process. Although previous video deblurring methods have achieved impressive…

cs.CV2024

PANet: A Physics-guided Parametric Augmentation Net for Image Dehazing by Hazing

Chih-Ling Chang, Fu-Jen Tsai, Zi-Ling Huang +2

Image dehazing faces challenges when dealing with hazy images in real-world scenarios. A huge domain gap between synthetic and real-world haze images degrades dehazing performance…

cs.CV2024

A self-supervised CNN for image watermark removal

Chunwei Tian, Menghua Zheng, Tiancai Jiao +3

Popular convolutional neural networks mainly use paired images in a supervised way for image watermark removal. However, watermarked images do not have reference images in the real…