17 citations · 80 across the 13 of their papers we have counts for
6 papers · 1 filter
HDRT: A Large-Scale Dataset for Infrared-Guided HDR Imaging
Jingchao Peng, Thomas Bashford-Rogers, Francesco Banterle +2
Capturing images with enough details to solve imaging tasks is a long-standing challenge in imaging, particularly due to the limitations of standard dynamic range (SDR) images whic…
Semantic Aware Diffusion Inverse Tone Mapping
Abhishek Goswami, Aru Ranjan Singh, Francesco Banterle +2
The range of real-world scene luminance is larger than the capture capability of many digital camera sensors which leads to details being lost in captured images, most typically in…
Virtual Category Learning: A Semi-Supervised Learning Method for Dense Prediction with Extremely Limited Labels
Changrui Chen, Jungong Han, Kurt Debattista
Due to the costliness of labelled data in real-world applications, semi-supervised learning, underpinned by pseudo labelling, is an appealing solution. However, handling confusing…
Semi-supervised Object Detection via Virtual Category Learning
Changrui Chen, Kurt Debattista, Jungong Han
Due to the costliness of labelled data in real-world applications, semi-supervised object detectors, underpinned by pseudo labelling, are appealing. However, handling confusing sam…
Deep HDR Hallucination for Inverse Tone Mapping
Demetris Marnerides, Thomas Bashford-Rogers, Kurt Debattista
Inverse Tone Mapping (ITM) methods attempt to reconstruct High Dynamic Range (HDR) information from Low Dynamic Range (LDR) image content. The dynamic range of well-exposed areas m…
ExpandNet: A Deep Convolutional Neural Network for High Dynamic Range Expansion from Low Dynamic Range Content
Demetris Marnerides, Thomas Bashford-Rogers, Jonathan Hatchett +1
High dynamic range (HDR) imaging provides the capability of handling real world lighting as opposed to the traditional low dynamic range (LDR) which struggles to accurately represe…