5.3k citations · 12.2k across the 85 of their papers we have counts for
12 papers · 1 filter
Geometry Sharing Network for 3D Point Cloud Classification and Segmentation
Mingye Xu, Zhipeng Zhou, Yu Qiao
In spite of the recent progresses on classifying 3D point cloud with deep CNNs, large geometric transformations like rotation and translation remain challenging problem and harm th…
Interactive Multi-Dimension Modulation with Dynamic Controllable Residual Learning for Image Restoration
Jingwen He, Chao Dong, Yu Qiao
Interactive image restoration aims to generate restored images by adjusting a controlling coefficient which determines the restoration level. Previous works are restricted in modul…
Learning Category Correlations for Multi-label Image Recognition with Graph Networks
Qing Li, Xiaojiang Peng, Yu Qiao +1
Multi-label image recognition is a task that predicts a set of object labels in an image. As the objects co-occur in the physical world, it is desirable to model label dependencies…
RankSRGAN: Generative Adversarial Networks with Ranker for Image Super-Resolution
Wenlong Zhang, Yihao Liu, Chao Dong +1
Generative Adversarial Networks (GAN) have demonstrated the potential to recover realistic details for single image super-resolution (SISR). To further improve the visual quality o…
Product Image Recognition with Guidance Learning and Noisy Supervision
Qing Li, Xiaojiang Peng, Liangliang Cao +3
This paper considers recognizing products from daily photos, which is an important problem in real-world applications but also challenging due to background clutters, category dive…
Bootstrap Model Ensemble and Rank Loss for Engagement Intensity Regression
Kai Wang, Jianfei Yang, Da Guo +3
This paper presents our approach for the engagement intensity regression task of EmotiW 2019. The task is to predict the engagement intensity value of a student when he or she is w…
Frame attention networks for facial expression recognition in videos
Debin Meng, Xiaojiang Peng, Kai Wang +1
The video-based facial expression recognition aims to classify a given video into several basic emotions. How to integrate facial features of individual frames is crucial for this…
Suppressing Model Overfitting for Image Super-Resolution Networks
Ruicheng Feng, Jinjin Gu, Yu Qiao +1
Large deep networks have demonstrated competitive performance in single image super-resolution (SISR), with a huge volume of data involved. However, in real-world scenarios, due to…
P2SGrad: Refined Gradients for Optimizing Deep Face Models
Xiao Zhang, Rui Zhao, Junjie Yan +4
Cosine-based softmax losses significantly improve the performance of deep face recognition networks. However, these losses always include sensitive hyper-parameters which can make…
AdaCos: Adaptively Scaling Cosine Logits for Effectively Learning Deep Face Representations
Xiao Zhang, Rui Zhao, Yu Qiao +2
The cosine-based softmax losses and their variants achieve great success in deep learning based face recognition. However, hyperparameter settings in these losses have significant…
Region Attention Networks for Pose and Occlusion Robust Facial Expression Recognition
Kai Wang, Xiaojiang Peng, Jianfei Yang +2
Occlusion and pose variations, which can change facial appearance significantly, are two major obstacles for automatic Facial Expression Recognition (FER). Though automatic FER has…
Modulating Image Restoration with Continual Levels via Adaptive Feature Modification Layers
Jingwen He, Chao Dong, Yu Qiao
In image restoration tasks, like denoising and super resolution, continual modulation of restoration levels is of great importance for real-world applications, but has failed most…