activity
20192022
most citedNTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results

11 citations · 16 across the 5 of their papers we have counts for

collaborators

6 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.CV202211 cited

NTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results

Eduardo Pérez-Pellitero, Sibi Catley-Chandar, Richard Shaw +85

This paper reviews the challenge on constrained high dynamic range (HDR) imaging that was part of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held in conj…

cs.LG20213 cited

Diversity-based Trajectory and Goal Selection with Hindsight Experience Replay

Tianhong Dai, Hengyan Liu, Kai Arulkumaran +2

Hindsight experience replay (HER) is a goal relabelling technique typically used with off-policy deep reinforcement learning algorithms to solve goal-oriented tasks; it is well sui…

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.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

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…