86 citations · 284 across the 24 of their papers we have counts for
13 papers · 2 filters
Miti-DETR: Object Detection based on Transformers with Mitigatory Self-Attention Convergence
Wenchi Ma, Tianxiao Zhang, Guanghui Wang
Object Detection with Transformers (DETR) and related works reach or even surpass the highly-optimized Faster-RCNN baseline with self-attention network architectures. Inspired by t…
Semantic Clustering based Deduction Learning for Image Recognition and Classification
Wenchi Ma, Xuemin Tu, Bo Luo +1
The paper proposes a semantic clustering based deduction learning by mimicking the learning and thinking process of human brains. Human beings can make judgments based on experienc…
Towards More Effective PRM-based Crowd Counting via A Multi-resolution Fusion and Attention Network
Usman Sajid, Guanghui Wang
The paper focuses on improving the recent plug-and-play patch rescaling module (PRM) based approaches for crowd counting. In order to make full use of the PRM potential and obtain…
A Discriminative Channel Diversification Network for Image Classification
Krushi Patel, Guanghui Wang
Channel attention mechanisms in convolutional neural networks have been proven to be effective in various computer vision tasks. However, the performance improvement comes with add…
Audio-Visual Transformer Based Crowd Counting
Usman Sajid, Xiangyu Chen, Hasan Sajid +2
Crowd estimation is a very challenging problem. The most recent study tries to exploit auditory information to aid the visual models, however, the performance is limited due to the…
Multiple Classifiers Based Maximum Classifier Discrepancy for Unsupervised Domain Adaptation
Yiju Yang, Taejoon Kim, Guanghui Wang
Adversarial training based on the maximum classifier discrepancy between two classifier structures has achieved great success in unsupervised domain adaptation tasks for image clas…