419 citations · 676 across the 36 of their papers we have counts for
36 papers
Weakly Supervised Semantic Segmentation for Large-Scale Point Cloud
Yachao Zhang, Zonghao Li, Yuan Xie +3
Existing methods for large-scale point cloud semantic segmentation require expensive, tedious and error-prone manual point-wise annotations. Intuitively, weakly supervised training…
Attentive pooling for Group Activity Recognition
Ding Li, Yuan Xie, Wensheng Zhang +2
In group activity recognition, hierarchical framework is widely adopted to represent the relationships between individuals and their corresponding group, and has achieved promising…
Structured Semantic Transfer for Multi-Label Recognition with Partial Labels
Tianshui Chen, Tao Pu, Hefeng Wu +2
Multi-label image recognition is a fundamental yet practical task because real-world images inherently possess multiple semantic labels. However, it is difficult to collect large-s…
Dual Reweighting Domain Generalization for Face Presentation Attack Detection
Shubao Liu, Ke-Yue Zhang, Taiping Yao +6
Face anti-spoofing approaches based on domain generalization (DG) have drawn growing attention due to their robustness for unseen scenarios. Previous methods treat each sample from…
Novelty Detection via Contrastive Learning with Negative Data Augmentation
Chengwei Chen, Yuan Xie, Shaohui Lin +5
Novelty detection is the process of determining whether a query example differs from the learned training distribution. Previous methods attempt to learn the representation of the…
Towards Compact Single Image Super-Resolution via Contrastive Self-distillation
Yanbo Wang, Shaohui Lin, Yanyun Qu +4
Convolutional neural networks (CNNs) are highly successful for super-resolution (SR) but often require sophisticated architectures with heavy memory cost and computational overhead…
Omni-supervised Point Cloud Segmentation via Gradual Receptive Field Component Reasoning
Jingyu Gong, Jiachen Xu, Xin Tan +4
Hidden features in neural network usually fail to learn informative representation for 3D segmentation as supervisions are only given on output prediction, while this can be solved…
Discrete-continuous Action Space Policy Gradient-based Attention for Image-Text Matching
Shiyang Yan, Li Yu, Yuan Xie
Image-text matching is an important multi-modal task with massive applications. It tries to match the image and the text with similar semantic information. Existing approaches do n…
Contrastive Learning for Compact Single Image Dehazing
Haiyan Wu, Yanyun Qu, Shaohui Lin +5
Single image dehazing is a challenging ill-posed problem due to the severe information degeneration. However, existing deep learning based dehazing methods only adopt clear images…
Farewell to Mutual Information: Variational Distillation for Cross-Modal Person Re-Identification
Xudong Tian, Zhizhong Zhang, Shaohui Lin +3
The Information Bottleneck (IB) provides an information theoretic principle for representation learning, by retaining all information relevant for predicting label while minimizing…
Boundary-Aware Geometric Encoding for Semantic Segmentation of Point Clouds
Jingyu Gong, Jiachen Xu, Xin Tan +4
Boundary information plays a significant role in 2D image segmentation, while usually being ignored in 3D point cloud segmentation where ambiguous features might be generated in fe…
AU-Expression Knowledge Constrained Representation Learning for Facial Expression Recognition
Tao Pu, Tianshui Chen, Yuan Xie +2
Recognizing human emotion/expressions automatically is quite an expected ability for intelligent robotics, as it can promote better communication and cooperation with humans. Curre…
Adversarial Graph Representation Adaptation for Cross-Domain Facial Expression Recognition
Yuan Xie, Tianshui Chen, Tao Pu +2
Data inconsistency and bias are inevitable among different facial expression recognition (FER) datasets due to subjective annotating process and different collecting conditions. Re…
Cross-Domain Facial Expression Recognition: A Unified Evaluation Benchmark and Adversarial Graph Learning
Tianshui Chen, Tao Pu, Hefeng Wu +3
To address the problem of data inconsistencies among different facial expression recognition (FER) datasets, many cross-domain FER methods (CD-FERs) have been extensively devised i…
Brain Tumor Anomaly Detection via Latent Regularized Adversarial Network
Nan Wang, Chengwei Chen, Yuan Xie +1
With the development of medical imaging technology, medical images have become an important basis for doctors to diagnose patients. The brain structure in the collected data is com…
Meta Segmentation Network for Ultra-Resolution Medical Images
Tong Wu, Yuan Xie, Yanyun Qu +2
Despite recent progress on semantic segmentation, there still exist huge challenges in medical ultra-resolution image segmentation. The methods based on multi-branch structure can…
Acoustic anomaly detection via latent regularized gaussian mixture generative adversarial networks
Chengwei Chen, Pan Chen, Lingyu Yang +4
Acoustic anomaly detection aims at distinguishing abnormal acoustic signals from the normal ones. It suffers from the class imbalance issue and the lacking in the abnormal instance…
Novelty Detection via Non-Adversarial Generative Network
Chengwei Chen, Wang Yuan, Yuan Xie +4
One-class novelty detection is the process of determining if a query example differs from the training examples (the target class). Most of previous strategies attempt to learn the…
Anomaly Detection by One Class Latent Regularized Networks
Chengwei Chen, Pan Chen, Haichuan Song +4
Anomaly detection is a fundamental problem in computer vision area with many real-world applications. Given a wide range of images belonging to the normal class, emerging from some…
SceneEncoder: Scene-Aware Semantic Segmentation of Point Clouds with A Learnable Scene Descriptor
Jiachen Xu, Jingyu Gong, Jie Zhou +3
Besides local features, global information plays an essential role in semantic segmentation, while recent works usually fail to explicitly extract the meaningful global information…
Semi-Supervised Video Salient Object Detection Using Pseudo-Labels
Pengxiang Yan, Guanbin Li, Yuan Xie +4
Deep learning-based video salient object detection has recently achieved great success with its performance significantly outperforming any other unsupervised methods. However, exi…
Knowledge Squeezed Adversarial Network Compression
Shu Changyong, Li Peng, Xie Yuan +3
Deep network compression has been achieved notable progress via knowledge distillation, where a teacher-student learning manner is adopted by using predetermined loss. Recently, mo…
Facial Landmark Machines: A Backbone-Branches Architecture with Progressive Representation Learning
Lingbo Liu, Guanbin Li, Yuan Xie +3
Facial landmark localization plays a critical role in face recognition and analysis. In this paper, we propose a novel cascaded backbone-branches fully convolutional neural network…
Bi-GANs-ST for Perceptual Image Super-resolution
Xiaotong Luo, Rong Chen, Yuan Xie +2
Image quality measurement is a critical problem for image super-resolution (SR) algorithms. Usually, they are evaluated by some well-known objective metrics, e.g., PSNR and SSIM, b…