activity
20162023
most citedMiti-DETR: Object Detection based on Transformers with Mitigatory Self-Attention Convergence

6 citations · 14 across the 11 of their papers we have counts for

collaborators
Showing cs.CVShow all

6 papers · 1 filter

cs.CV20216 cited

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…

cs.CV20211 cited

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…

cs.CV2021

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…

cs.CV2021

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…

cs.CV20164 cited

Real-Time Visual Tracking: Promoting the Robustness of Correlation Filter Learning

Yao Sui, Ziming Zhang, Guanghui Wang +2

Correlation filtering based tracking model has received lots of attention and achieved great success in real-time tracking, however, the lost function in current correlation filter…

cs.CV2016

Robust Structure from Motion in the Presence of Outliers and Missing Data

Guanghui Wang

Structure from motion is an import theme in computer vision. Although great progress has been made both in theory and applications, most of the algorithms only work for static scen…