1.2k citations · 2.7k across the 112 of their papers we have counts for
16 papers · 1 filter
Gyroscope-Aided Motion Deblurring with Deep Networks
Janne Mustaniemi, Juho Kannala, Simo Särkkä +2
We propose a deblurring method that incorporates gyroscope measurements into a convolutional neural network (CNN). With the help of such measurements, it can handle extremely stron…
LSD -- Joint Denoising and Deblurring of Short and Long Exposure Images with CNNs
Janne Mustaniemi, Juho Kannala, Jiri Matas +2
The paper addresses the problem of acquiring high-quality photographs with handheld smartphone cameras in low-light imaging conditions. We propose an approach based on capturing pa…
DGC-Net: Dense Geometric Correspondence Network
Iaroslav Melekhov, Aleksei Tiulpin, Torsten Sattler +3
This paper addresses the challenge of dense pixel correspondence estimation between two images. This problem is closely related to optical flow estimation task where ConvNets (CNNs…
Scene Coordinate Regression with Angle-Based Reprojection Loss for Camera Relocalization
Xiaotian Li, Juha Ylioinas, Jakob Verbeek +1
Image-based camera relocalization is an important problem in computer vision and robotics. Recent works utilize convolutional neural networks (CNNs) to regress for pixels in a quer…
Deep Learning Based Speed Estimation for Constraining Strapdown Inertial Navigation on Smartphones
Santiago Cortés, Arno Solin, Juho Kannala
Strapdown inertial navigation systems are sensitive to the quality of the data provided by the accelerometer and gyroscope. Low-grade IMUs in handheld smart-devices pose a problem…
Leveraging Unlabeled Whole-Slide-Images for Mitosis Detection
Saad Ullah Akram, Talha Qaiser, Simon Graham +3
Mitosis count is an important biomarker for prognosis of various cancers. At present, pathologists typically perform manual counting on a few selected regions of interest in breast…
ADVIO: An authentic dataset for visual-inertial odometry
Santiago Cortés, Arno Solin, Esa Rahtu +1
The lack of realistic and open benchmarking datasets for pedestrian visual-inertial odometry has made it hard to pinpoint differences in published methods. Existing datasets either…
Learning Representations for Soft Skill Matching
Luiza Sayfullina, Eric Malmi, Juho Kannala
Employers actively look for talents having not only specific hard skills but also various soft skills. To analyze the soft skill demands on the job market, it is important to be ab…
Pioneer Networks: Progressively Growing Generative Autoencoder
Ari Heljakka, Arno Solin, Juho Kannala
We introduce a novel generative autoencoder network model that learns to encode and reconstruct images with high quality and resolution, and supports smooth random sampling from th…
Robust Gyroscope-Aided Camera Self-Calibration
Santiago Cortés Reina, Arno Solin, Juho Kannala
Camera calibration for estimating the intrinsic parameters and lens distortion is a prerequisite for various monocular vision applications including feature tracking and video stab…
Fast Motion Deblurring for Feature Detection and Matching Using Inertial Measurements
Janne Mustaniemi, Juho Kannala, Simo Särkkä +2
Many computer vision and image processing applications rely on local features. It is well-known that motion blur decreases the performance of traditional feature detectors and desc…
Learning image-to-image translation using paired and unpaired training samples
Soumya Tripathy, Juho Kannala, Esa Rahtu
Image-to-image translation is a general name for a task where an image from one domain is converted to a corresponding image in another domain, given sufficient training data. Trad…
Accurate 3-D Reconstruction with RGB-D Cameras using Depth Map Fusion and Pose Refinement
Markus Ylimäki, Juho Kannala, Janne Heikkilä
Depth map fusion is an essential part in both stereo and RGB-D based 3-D reconstruction pipelines. Whether produced with a passive stereo reconstruction or using an active depth se…
Devon: Deformable Volume Network for Learning Optical Flow
Yao Lu, Jack Valmadre, Heng Wang +3
State-of-the-art neural network models estimate large displacement optical flow in multi-resolution and use warping to propagate the estimation between two resolutions. Despite the…
Recursive Chaining of Reversible Image-to-image Translators For Face Aging
Ari Heljakka, Arno Solin, Juho Kannala
This paper addresses the modeling and simulation of progressive changes over time, such as human face aging. By treating the age phases as a sequence of image domains, we construct…
Full-Frame Scene Coordinate Regression for Image-Based Localization
Xiaotian Li, Juha Ylioinas, Juho Kannala
Image-based localization, or camera relocalization, is a fundamental problem in computer vision and robotics, and it refers to estimating camera pose from an image. Recent state-of…