103 citations · 446 across the 30 of their papers we have counts for
18 papers · 1 filter
TDMD: A Database for Dynamic Color Mesh Subjective and Objective Quality Explorations
Qi Yang, Joel Jung, Timon Deschamps +2
Dynamic colored meshes (DCM) are widely used in various applications; however, these meshes may undergo different processes, such as compression or transmission, which can distort…
Reconstruction Distortion of Learned Image Compression with Imperceptible Perturbations
Yang Sui, Zhuohang Li, Ding Ding +4
Learned Image Compression (LIC) has recently become the trending technique for image transmission due to its notable performance. Despite its popularity, the robustness of LIC with…
Coarse-to-fine Deep Video Coding with Hyperprior-guided Mode Prediction
Zhihao Hu, Guo Lu, Jinyang Guo +3
The previous deep video compression approaches only use the single scale motion compensation strategy and rarely adopt the mode prediction technique from the traditional standards…
Recent Standard Development Activities on Video Coding for Machines
Wen Gao, Shan Liu, Xiaozhong Xu +3
In recent years, video data has dominated internet traffic and becomes one of the major data formats. With the emerging 5G and internet of things (IoT) technologies, more and more…
SSD-GAN: Measuring the Realness in the Spatial and Spectral Domains
Yuanqi Chen, Ge Li, Cece Jin +2
This paper observes that there is an issue of high frequencies missing in the discriminator of standard GAN, and we reveal it stems from downsampling layers employed in the network…
Unsupervised Point Cloud Registration via Salient Points Analysis (SPA)
Pranav Kadam, Min Zhang, Shan Liu +1
An unsupervised point cloud registration method, called salient points analysis (SPA), is proposed in this work. The proposed SPA method can register two point clouds effectively u…
Unsupervised Feedforward Feature (UFF) Learning for Point Cloud Classification and Segmentation
Min Zhang, Pranav Kadam, Shan Liu +1
In contrast to supervised backpropagation-based feature learning in deep neural networks (DNNs), an unsupervised feedforward feature (UFF) learning scheme for joint classification…
Deep Spatial Transformation for Pose-Guided Person Image Generation and Animation
Yurui Ren, Ge Li, Shan Liu +1
Pose-guided person image generation and animation aim to transform a source person image to target poses. These tasks require spatial manipulation of source data. However, Convolut…
Toward Zero-Shot Unsupervised Image-to-Image Translation
Yuanqi Chen, Xiaoming Yu, Shan Liu +1
Recent studies have shown remarkable success in unsupervised image-to-image translation. However, if there has no access to enough images in target classes, learning a mapping from…
Learning Model-Blind Temporal Denoisers without Ground Truths
Yanghao Li, Bichuan Guo, Jiangtao Wen +3
Denoisers trained with synthetic data often fail to cope with the diversity of unknown noises, giving way to methods that can adapt to existing noise without knowing its ground tru…
PointHop++: A Lightweight Learning Model on Point Sets for 3D Classification
Min Zhang, Yifan Wang, Pranav Kadam +2
The PointHop method was recently proposed by Zhang et al. for 3D point cloud classification with unsupervised feature extraction. It has an extremely low training complexity while…
RoIMix: Proposal-Fusion among Multiple Images for Underwater Object Detection
Wei-Hong Lin, Jia-Xing Zhong, Shan Liu +2
Generic object detection algorithms have proven their excellent performance in recent years. However, object detection on underwater datasets is still less explored. In contrast to…
Multi-mapping Image-to-Image Translation via Learning Disentanglement
Xiaoming Yu, Yuanqi Chen, Thomas Li +2
Recent advances of image-to-image translation focus on learning the one-to-many mapping from two aspects: multi-modal translation and multi-domain translation. However, the existin…
StructureFlow: Image Inpainting via Structure-aware Appearance Flow
Yurui Ren, Xiaoming Yu, Ruonan Zhang +3
Image inpainting techniques have shown significant improvements by using deep neural networks recently. However, most of them may either fail to reconstruct reasonable structures o…
PointHop: An Explainable Machine Learning Method for Point Cloud Classification
Min Zhang, Haoxuan You, Pranav Kadam +2
An explainable machine learning method for point cloud classification, called the PointHop method, is proposed in this work. The PointHop method consists of two stages: 1) local-to…
Deep AutoEncoder-based Lossy Geometry Compression for Point Clouds
Wei Yan, Yiting shao, Shan Liu +3
Point cloud is a fundamental 3D representation which is widely used in real world applications such as autonomous driving. As a newly-developed media format which is characterized…
Graph Convolutional Label Noise Cleaner: Train a Plug-and-play Action Classifier for Anomaly Detection
Jia-Xing Zhong, Nannan Li, Weijie Kong +3
Video anomaly detection under weak labels is formulated as a typical multiple-instance learning problem in previous works. In this paper, we provide a new perspective, i.e., a supe…
BLP -- Boundary Likelihood Pinpointing Networks for Accurate Temporal Action Localization
Weijie Kong, Nannan Li, Shan Liu +2
Despite tremendous progress achieved in temporal action detection, state-of-the-art methods still suffer from the sharp performance deterioration when localizing the starting and e…