11 citations · 24 across the 7 of their papers we have counts for
15 papers
Searching for Network Width with Bilaterally Coupled Network
Xiu Su, Shan You, Jiyang Xie +4
Searching for a more compact network width recently serves as an effective way of channel pruning for the deployment of convolutional neural networks (CNNs) under hardware constrai…
Structured DropConnect for Uncertainty Inference in Image Classification
Wenqing Zheng, Jiyang Xie, Weidong Liu +1
With the complexity of the network structure, uncertainty inference has become an important task to improve the classification accuracy for artificial intelligence systems. For ima…
Cross-layer Navigation Convolutional Neural Network for Fine-grained Visual Classification
Chenyu Guo, Jiyang Xie, Kongming Liang +2
Fine-grained visual classification (FGVC) aims to classify sub-classes of objects in the same super-class (e.g., species of birds, models of cars). For the FGVC tasks, the essentia…
DF^2AM: Dual-level Feature Fusion and Affinity Modeling for RGB-Infrared Cross-modality Person Re-identification
Junhui Yin, Zhanyu Ma, Jiyang Xie +3
RGB-infrared person re-identification is a challenging task due to the intra-class variations and cross-modality discrepancy. Existing works mainly focus on learning modality-share…
Unsupervised Person Re-identification via Simultaneous Clustering and Consistency Learning
Junhui Yin, Jiayan Qiu, Siqing Zhang +3
Unsupervised person re-identification (re-ID) has become an important topic due to its potential to resolve the scalability problem of supervised re-ID models. However, existing me…
Grad-CAM guided channel-spatial attention module for fine-grained visual classification
Shuai Xu, Dongliang Chang, Jiyang Xie +1
Fine-grained visual classification (FGVC) is becoming an important research field, due to its wide applications and the rapid development of computer vision technologies. The curre…