113 citations · 405 across the 34 of their papers we have counts for
9 papers · 1 filter
Benchmarking Shadow Removal for Facial Landmark Detection and Beyond
Lan Fu, Qing Guo, Felix Juefei-Xu +4
Facial landmark detection is a very fundamental and significant vision task with many important applications. In practice, facial landmark detection can be affected by a lot of nat…
ATLANTIS: A Benchmark for Semantic Segmentation of Waterbody Images
Seyed Mohammad Hassan Erfani, Zhenyao Wu, Xinyi Wu +2
Vision-based semantic segmentation of waterbodies and nearby related objects provides important information for managing water resources and handling flooding emergency. However, t…
VIL-100: A New Dataset and A Baseline Model for Video Instance Lane Detection
Yujun Zhang, Lei Zhu, Wei Feng +5
Lane detection plays a key role in autonomous driving. While car cameras always take streaming videos on the way, current lane detection works mainly focus on individual images (fr…
CPNet: Cycle Prototype Network for Weakly-supervised 3D Renal Compartments Segmentation on CT Images
Song Wang, Yuting He, Youyong Kong +7
Renal compartment segmentation on CT images targets on extracting the 3D structure of renal compartments from abdominal CTA images and is of great significance to the diagnosis and…
JPGNet: Joint Predictive Filtering and Generative Network for Image Inpainting
Qing Guo, Xiaoguang Li, Felix Juefei-Xu +3
Image inpainting aims to restore the missing regions of corrupted images and make the recovery result identical to the originally complete image, which is different from the common…
Let There be Light: Improved Traffic Surveillance via Detail Preserving Night-to-Day Transfer
Lan Fu, Hongkai Yu, Felix Juefei-Xu +3
In recent years, image and video surveillance have made considerable progresses to the Intelligent Transportation Systems (ITS) with the help of deep Convolutional Neural Networks…
Sparta: Spatially Attentive and Adversarially Robust Activation
Qing Guo, Felix Juefei-Xu, Changqing Zhou +3
Adversarial training (AT) is one of the most effective ways for improving the robustness of deep convolution neural networks (CNNs). Just like common network training, the effectiv…
DANNet: A One-Stage Domain Adaptation Network for Unsupervised Nighttime Semantic Segmentation
Xinyi Wu, Zhenyao Wu, Hao Guo +2
Semantic segmentation of nighttime images plays an equally important role as that of daytime images in autonomous driving, but the former is much more challenging due to poor illum…
From Shadow Generation to Shadow Removal
Zhihao Liu, Hui Yin, Xinyi Wu +3
Shadow removal is a computer-vision task that aims to restore the image content in shadow regions. While almost all recent shadow-removal methods require shadow-free images for tra…