1.1k citations · 2.6k across the 75 of their papers we have counts for
17 papers · 1 filter
Globally Optimal Relative Pose Estimation with Gravity Prior
Yaqing Ding, Daniel Barath, Jian Yang +2
Smartphones, tablets and camera systems used, e.g., in cars and UAVs, are typically equipped with IMUs (inertial measurement units) that can measure the gravity vector accurately.…
They are Not Completely Useless: Towards Recycling Transferable Unlabeled Data for Class-Mismatched Semi-Supervised Learning
Zhuo Huang, Ying Tai, Chengjie Wang +2
Semi-Supervised Learning (SSL) with mismatched classes deals with the problem that the classes-of-interests in the limited labeled data is only a subset of the classes in massive u…
Progressive Training of Multi-level Wavelet Residual Networks for Image Denoising
Yali Peng, Yue Cao, Shigang Liu +2
Recent years have witnessed the great success of deep convolutional neural networks (CNNs) in image denoising. Albeit deeper network and larger model capacity generally benefit per…
Multi-Level Graph Convolutional Network with Automatic Graph Learning for Hyperspectral Image Classification
Sheng Wan, Chen Gong, Shirui Pan +2
Nowadays, deep learning methods, especially the Graph Convolutional Network (GCN), have shown impressive performance in hyperspectral image (HSI) classification. However, the curre…
Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Learning
Sheng Wan, Shirui Pan, Jian Yang +1
Graph-based Semi-Supervised Learning (SSL) aims to transfer the labels of a handful of labeled data to the remaining massive unlabeled data via a graph. As one of the most popular…
Frontier Detection and Reachability Analysis for Efficient 2D Graph-SLAM Based Active Exploration
Zezhou Sun, Banghe Wu, Cheng-Zhong Xu +3
We propose an integrated approach to active exploration by exploiting the Cartographer method as the base SLAM module for submap creation and performing efficient frontier detectio…
Spatial Transformer Point Convolution
Yuan Fang, Chunyan Xu, Zhen Cui +2
Point clouds are unstructured and unordered in the embedded 3D space. In order to produce consistent responses under different permutation layouts, most existing methods aggregate…
Interest-Behaviour Multiplicative Network for Resource-limited Recommendation
Qianliang Wu, Tong Zhang, Zhen Cui +1
Resource constraints, e.g. limited product inventory or financial strength, may affect consumers' choices or preferences in some recommendation tasks but are usually ignored in pre…
Instance-Aware Graph Convolutional Network for Multi-Label Classification
Yun Wang, Tong Zhang, Zhen Cui +2
Graph convolutional neural network (GCN) has effectively boosted the multi-label image recognition task by introducing label dependencies based on statistical label co-occurrence o…
Graph Wasserstein Correlation Analysis for Movie Retrieval
Xueya Zhang, Tong Zhang, Xiaobin Hong +2
Movie graphs play an important role to bridge heterogenous modalities of videos and texts in human-centric retrieval. In this work, we propose Graph Wasserstein Correlation Analysi…
Localizing Anomalies from Weakly-Labeled Videos
Hui Lv, Chuanwei Zhou, Chunyan Xu +2
Video anomaly detection under video-level labels is currently a challenging task. Previous works have made progresses on discriminating whether a video sequencecontains anomalies.…
Cascaded Non-local Neural Network for Point Cloud Semantic Segmentation
Mingmei Cheng, Le Hui, Jin Xie +2
In this paper, we propose a cascaded non-local neural network for point cloud segmentation. The proposed network aims to build the long-range dependencies of point clouds for the a…
Progressive Point Cloud Deconvolution Generation Network
Le Hui, Rui Xu, Jin Xie +2
In this paper, we propose an effective point cloud generation method, which can generate multi-resolution point clouds of the same shape from a latent vector. Specifically, we deve…
Learning the Redundancy-free Features for Generalized Zero-Shot Object Recognition
Zongyan Han, Zhenyong Fu, Jian Yang
Zero-shot object recognition or zero-shot learning aims to transfer the object recognition ability among the semantically related categories, such as fine-grained animal or bird sp…
NTIRE 2020 Challenge on Image Demoireing: Methods and Results
Shanxin Yuan, Radu Timofte, Ales Leonardis +43
This paper reviews the Challenge on Image Demoireing that was part of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held in conjunction with CVPR 2020. Demo…
Network Cooperation with Progressive Disambiguation for Partial Label Learning
Yao Yao, Chen Gong, Jiehui Deng +1
Partial Label Learning (PLL) aims to train a classifier when each training instance is associated with a set of candidate labels, among which only one is correct but is not accessi…
Graph Inference Learning for Semi-supervised Classification
Chunyan Xu, Zhen Cui, Xiaobin Hong +3
In this work, we address semi-supervised classification of graph data, where the categories of those unlabeled nodes are inferred from labeled nodes as well as graph structures. Re…