57 citations · 260 across the 30 of their papers we have counts for
30 papers
Learning Restoration is Not Enough: Transfering Identical Mapping for Single-Image Shadow Removal
Xiaoguang Li, Qing Guo, Pingping Cai +3
Shadow removal is to restore shadow regions to their shadow-free counterparts while leaving non-shadow regions unchanged. State-of-the-art shadow removal methods train deep neural…
Leveraging Inpainting for Single-Image Shadow Removal
Xiaoguang Li, Qing Guo, Rabab Abdelfattah +4
Fully-supervised shadow removal methods achieve the best restoration qualities on public datasets but still generate some shadow remnants. One of the reasons is the lack of large-s…
Structure-Informed Shadow Removal Networks
Yuhao Liu, Qing Guo, Lan Fu +5
Existing deep learning-based shadow removal methods still produce images with shadow remnants. These shadow remnants typically exist in homogeneous regions with low-intensity value…
From a Bird's Eye View to See: Joint Camera and Subject Registration without the Camera Calibration
Zekun Qian, Ruize Han, Wei Feng +2
We tackle a new problem of multi-view camera and subject registration in the bird's eye view (BEV) without pre-given camera calibration. This is a very challenging problem since it…
MISF: Multi-level Interactive Siamese Filtering for High-Fidelity Image Inpainting
Xiaoguang Li, Qing Guo, Di Lin +3
Although achieving significant progress, existing deep generative inpainting methods are far from real-world applications due to the low generalization across different scenes. As…
Self-supervised Social Relation Representation for Human Group Detection
Jiacheng Li, Ruize Han, Haomin Yan +3
Human group detection, which splits crowd of people into groups, is an important step for video-based human social activity analysis. The core of human group detection is the human…
Uncertainty-Aware Cascaded Dilation Filtering for High-Efficiency Deraining
Qing Guo, Jingyang Sun, Felix Juefei-Xu +4
Deraining is a significant and fundamental computer vision task, aiming to remove the rain streaks and accumulations in an image or video captured under a rainy day. Existing derai…
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…
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…
From Synthetic to Real: Image Dehazing Collaborating with Unlabeled Real Data
Ye Liu, Lei Zhu, Shunda Pei +5
Single image dehazing is a challenging task, for which the domain shift between synthetic training data and real-world testing images usually leads to degradation of existing metho…
Adversarial Relighting Against Face Recognition
Qian Zhang, Qing Guo, Ruijun Gao +3
Deep face recognition (FR) has achieved significantly high accuracy on several challenging datasets and fosters successful real-world applications, even showing high robustness to…
CarveNet: Carving Point-Block for Complex 3D Shape Completion
Qing Guo, Zhijie Wang, Felix Juefei-Xu +4
3D point cloud completion is very challenging because it heavily relies on the accurate understanding of the complex 3D shapes (e.g., high-curvature, concave/convex, and hollowed-o…
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…
AdvHaze: Adversarial Haze Attack
Ruijun Gao, Qing Guo, Felix Juefei-Xu +2
In recent years, adversarial attacks have drawn more attention for their value on evaluating and improving the robustness of machine learning models, especially, neural network mod…
Auto-Exposure Fusion for Single-Image Shadow Removal
Lan Fu, Changqing Zhou, Qing Guo +5
Shadow removal is still a challenging task due to its inherent background-dependent and spatial-variant properties, leading to unknown and diverse shadow patterns. Even powerful st…
Multi-Domain Multi-Task Rehearsal for Lifelong Learning
Fan Lyu, Shuai Wang, Wei Feng +3
Rehearsal, seeking to remind the model by storing old knowledge in lifelong learning, is one of the most effective ways to mitigate catastrophic forgetting, i.e., biased forgetting…
EfficientDeRain: Learning Pixel-wise Dilation Filtering for High-Efficiency Single-Image Deraining
Qing Guo, Jingyang Sun, Felix Juefei-Xu +4
Single-image deraining is rather challenging due to the unknown rain model. Existing methods often make specific assumptions of the rain model, which can hardly cover many diverse…
Can You Spot the Chameleon? Adversarially Camouflaging Images from Co-Salient Object Detection
Ruijun Gao, Qing Guo, Felix Juefei-Xu +5
Co-salient object detection (CoSOD) has recently achieved significant progress and played a key role in retrieval-related tasks. However, it inevitably poses an entirely new safety…
Pasadena: Perceptually Aware and Stealthy Adversarial Denoise Attack
Yupeng Cheng, Qing Guo, Felix Juefei-Xu +4
Image denoising can remove natural noise that widely exists in images captured by multimedia devices due to low-quality imaging sensors, unstable image transmission processes, or l…
DeepRhythm: Exposing DeepFakes with Attentional Visual Heartbeat Rhythms
Hua Qi, Qing Guo, Felix Juefei-Xu +5
As the GAN-based face image and video generation techniques, widely known as DeepFakes, have become more and more matured and realistic, there comes a pressing and urgent demand fo…
Modeling Cross-view Interaction Consistency for Paired Egocentric Interaction Recognition
Zhongguo Li, Fan Lyu, Wei Feng +1
With the development of Augmented Reality (AR), egocentric action recognition (EAR) plays important role in accurately understanding demands from the user. However, EAR is designed…
MUTATT: Visual-Textual Mutual Guidance for Referring Expression Comprehension
Shuai Wang, Fan Lyu, Wei Feng +1
Referring expression comprehension (REC) aims to localize a text-related region in a given image by a referring expression in natural language. Existing methods focus on how to bui…
Active Lighting Recurrence by Parallel Lighting Analogy for Fine-Grained Change Detection
Qian Zhang, Wei Feng, Liang Wan +3
This paper studies a new problem, namely active lighting recurrence (ALR) that physically relocalizes a light source to reproduce the lighting condition from single reference image…
Watch out! Motion is Blurring the Vision of Your Deep Neural Networks
Qing Guo, Felix Juefei-Xu, Xiaofei Xie +5
The state-of-the-art deep neural networks (DNNs) are vulnerable against adversarial examples with additive random-like noise perturbations. While such examples are hardly found in…