activity
20182022
most citedTowards Automated Polyp Segmentation Using Weakly- and Semi-Supervised Learning and Deformable Transformers

2 citations · 3 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CV20222 cited

Towards Automated Polyp Segmentation Using Weakly- and Semi-Supervised Learning and Deformable Transformers

Guangyu Ren, Michalis Lazarou, Jing Yuan +1

Polyp segmentation is a crucial step towards computer-aided diagnosis of colorectal cancer. However, most of the polyp segmentation methods require pixel-wise annotated datasets. A…

cs.CV2021

Progressive Multi-scale Fusion Network for RGB-D Salient Object Detection

Guangyu Ren, Yanchu Xie, Tianhong Dai +1

Salient object detection(SOD) aims at locating the most significant object within a given image. In recent years, great progress has been made in applying SOD on many vision tasks.…

cs.CV20211 cited

Few-shot learning via tensor hallucination

Michalis Lazarou, Yannis Avrithis, Tania Stathaki

Few-shot classification addresses the challenge of classifying examples given only limited labeled data. A powerful approach is to go beyond data augmentation, towards data synthes…

cs.CV2020

Salient Object Detection Combining a Self-attention Module and a Feature Pyramid Network

Guangyu Ren, Tianhong Dai, Panagiotis Barmpoutis +1

Salient object detection has achieved great improvement by using the Fully Convolution Network (FCN). However, the FCN-based U-shape architecture may cause the dilution problem in…

cs.CV2019

Coupled Network for Robust Pedestrian Detection with Gated Multi-Layer Feature Extraction and Deformable Occlusion Handling

Tianrui Liu, Wenhan Luo, Lin Ma +3

Pedestrian detection methods have been significantly improved with the development of deep convolutional neural networks. Nevertheless, detecting small-scaled pedestrians and occlu…

cs.CV2019

Gated Multi-layer Convolutional Feature Extraction Network for Robust Pedestrian Detection

Tianrui Liu, Jun-Jie Huang, Tianhong Dai +2

Pedestrian detection methods have been significantly improved with the development of deep convolutional neural networks. Nevertheless, robustly detecting pedestrians with a large…