192 citations · 296 across the 11 of their papers we have counts for
16 papers
Calibrating Class Activation Maps for Long-Tailed Visual Recognition
Chi Zhang, Guosheng Lin, Lvlong Lai +2
Real-world visual recognition problems often exhibit long-tailed distributions, where the amount of data for learning in different categories shows significant imbalance. Standard…
MV-TON: Memory-based Video Virtual Try-on network
Xiaojing Zhong, Zhonghua Wu, Taizhe Tan +2
With the development of Generative Adversarial Network, image-based virtual try-on methods have made great progress. However, limited work has explored the task of video-based virt…
Context Decoupling Augmentation for Weakly Supervised Semantic Segmentation
Yukun Su, Ruizhou Sun, Guosheng Lin +1
Data augmentation is vital for deep learning neural networks. By providing massive training samples, it helps to improve the generalization ability of the model. Weakly supervised…
StackRec: Efficient Training of Very Deep Sequential Recommender Models by Iterative Stacking
Jiachun Wang, Fajie Yuan, Jian Chen +4
Deep learning has brought great progress for the sequential recommendation (SR) tasks. With advanced network architectures, sequential recommender models can be stacked with many h…
Double Forward Propagation for Memorized Batch Normalization
Yong Guo, Qingyao Wu, Chaorui Deng +2
Batch Normalization (BN) has been a standard component in designing deep neural networks (DNNs). Although the standard BN can significantly accelerate the training of DNNs and impr…
Graph Edit Distance Reward: Learning to Edit Scene Graph
Lichang Chen, Guosheng Lin, Shijie Wang +1
Scene Graph, as a vital tool to bridge the gap between language domain and image domain, has been widely adopted in the cross-modality task like VQA. In this paper, we propose a ne…