18 citations · 72 across the 34 of their papers we have counts for
6 papers · 1 filter
Content-Diverse Comparisons improve IQA
William Thong, Jose Costa Pereira, Sarah Parisot +2
Image quality assessment (IQA) forms a natural and often straightforward undertaking for humans, yet effective automation of the task remains highly challenging. Recent metrics fro…
Is my Depth Ground-Truth Good Enough? HAMMER -- Highly Accurate Multi-Modal Dataset for DEnse 3D Scene Regression
HyunJun Jung, Patrick Ruhkamp, Guangyao Zhai +9
Depth estimation is a core task in 3D computer vision. Recent methods investigate the task of monocular depth trained with various depth sensor modalities. Every sensor has its adv…
Collaborative Learning for Hand and Object Reconstruction with Attention-guided Graph Convolution
Tze Ho Elden Tse, Kwang In Kim, Ales Leonardis +1
Estimating the pose and shape of hands and objects under interaction finds numerous applications including augmented and virtual reality. Existing approaches for hand and object re…
HDR Reconstruction from Bracketed Exposures and Events
Richard Shaw, Sibi Catley-Chandar, Ales Leonardis +1
Reconstruction of high-quality HDR images is at the core of modern computational photography. Significant progress has been made with multi-frame HDR reconstruction methods, produc…
Self-supervised HDR Imaging from Motion and Exposure Cues
Michal Nazarczuk, Sibi Catley-Chandar, Ales Leonardis +1
Recent High Dynamic Range (HDR) techniques extend the capabilities of current cameras where scenes with a wide range of illumination can not be accurately captured with a single lo…
Repurposing Existing Deep Networks for Caption and Aesthetic-Guided Image Cropping
Nora Horanyi, Kedi Xia, Kwang Moo Yi +3
We propose a novel optimization framework that crops a given image based on user description and aesthetics. Unlike existing image cropping methods, where one typically trains a de…