57 citations · 133 across the 14 of their papers we have counts for
14 papers
CopyRNeRF: Protecting the CopyRight of Neural Radiance Fields
Ziyuan Luo, Qing Guo, Ka Chun Cheung +2
Neural Radiance Fields (NeRF) have the potential to be a major representation of media. Since training a NeRF has never been an easy task, the protection of its model copyright sho…
SuperInpaint: Learning Detail-Enhanced Attentional Implicit Representation for Super-resolutional Image Inpainting
Canyu Zhang, Qing Guo, Xiaoguang Li +4
In this work, we introduce a challenging image restoration task, referred to as SuperInpaint, which aims to reconstruct missing regions in low-resolution images and generate comple…
Defense against Adversarial Cloud Attack on Remote Sensing Salient Object Detection
Huiming Sun, Lan Fu, Jinlong Li +5
Detecting the salient objects in a remote sensing image has wide applications for the interdisciplinary research. Many existing deep learning methods have been proposed for Salient…
CDUL: CLIP-Driven Unsupervised Learning for Multi-Label Image Classification
Rabab Abdelfattah, Qing Guo, Xiaoguang Li +2
This paper presents a CLIP-based unsupervised learning method for annotation-free multi-label image classification, including three stages: initialization, training, and inference.…
RXFOOD: Plug-in RGB-X Fusion for Object of Interest Detection
Jin Ma, Jinlong Li, Qing Guo +3
The emergence of different sensors (Near-Infrared, Depth, etc.) is a remedy for the limited application scenarios of traditional RGB camera. The RGB-X tasks, which rely on RGB inpu…
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…
Coarse-to-fine Task-driven Inpainting for Geoscience Images
Huiming Sun, Jin Ma, Qing Guo +4
The processing and recognition of geoscience images have wide applications. Most of existing researches focus on understanding the high-quality geoscience images by assuming that a…
Single Object Tracking Research: A Survey
Ruize Han, Wei Feng, Qing Guo +1
Visual object tracking is an important task in computer vision, which has many real-world applications, e.g., video surveillance, visual navigation. Visual object tracking also has…
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…
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…
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…
SPARK: Spatial-aware Online Incremental Attack Against Visual Tracking
Qing Guo, Xiaofei Xie, Felix Juefei-Xu +5
Adversarial attacks of deep neural networks have been intensively studied on image, audio, natural language, patch, and pixel classification tasks. Nevertheless, as a typical, whil…