1.2k citations · 2.7k across the 112 of their papers we have counts for
20 papers · 1 filter
Deep Automodulators
Ari Heljakka, Yuxin Hou, Juho Kannala +1
We introduce a new category of generative autoencoders called automodulators. These networks can faithfully reproduce individual real-world input images like regular autoencoders,…
Regularizing Model-Based Planning with Energy-Based Models
Rinu Boney, Juho Kannala, Alexander Ilin
Model-based reinforcement learning could enable sample-efficient learning by quickly acquiring rich knowledge about the world and using it to improve behaviour without additional d…
GraphMix: Improved Training of GNNs for Semi-Supervised Learning
Vikas Verma, Meng Qu, Kenji Kawaguchi +4
We present GraphMix, a regularization method for Graph Neural Network based semi-supervised object classification, whereby we propose to train a fully-connected network jointly wit…
Hierarchical Scene Coordinate Classification and Regression for Visual Localization
Xiaotian Li, Shuzhe Wang, Yi Zhao +2
Visual localization is critical to many applications in computer vision and robotics. To address single-image RGB localization, state-of-the-art feature-based methods match local d…
Iterative Path Reconstruction for Large-Scale Inertial Navigation on Smartphones
Santiago Cortés Reina, Yuxin Hou, Juho Kannala +1
Modern smartphones have all the sensing capabilities required for accurate and robust navigation and tracking. In specific environments some data streams may be absent, less reliab…
Interpolated Adversarial Training: Achieving Robust Neural Networks without Sacrificing Too Much Accuracy
Alex Lamb, Vikas Verma, Kenji Kawaguchi +4
Adversarial robustness has become a central goal in deep learning, both in the theory and the practice. However, successful methods to improve the adversarial robustness (such as a…
DAVE: A Deep Audio-Visual Embedding for Dynamic Saliency Prediction
Hamed R. Tavakoli, Ali Borji, Esa Rahtu +1
This paper studies audio-visual deep saliency prediction. It introduces a conceptually simple and effective Deep Audio-Visual Embedding for dynamic saliency prediction dubbed ``DAV…
Automated Structure Discovery in Atomic Force Microscopy
Benjamin Alldritt, Prokop Hapala, Niko Oinonena +7
Atomic force microscopy (AFM) with molecule-functionalized tips has emerged as the primary experimental technique for probing the atomic structure of organic molecules on surfaces.…
Digging Deeper into Egocentric Gaze Prediction
Hamed R. Tavakoli, Esa Rahtu, Juho Kannala +1
This paper digs deeper into factors that influence egocentric gaze. Instead of training deep models for this purpose in a blind manner, we propose to inspect factors that contribut…
CubiCasa5K: A Dataset and an Improved Multi-Task Model for Floorplan Image Analysis
Ahti Kalervo, Juha Ylioinas, Markus Häikiö +2
Better understanding and modelling of building interiors and the emergence of more impressive AR/VR technology has brought up the need for automatic parsing of floorplan images. Ho…
Geometric Image Correspondence Verification by Dense Pixel Matching
Zakaria Laskar, Iaroslav Melekhov, Hamed R. Tavakoli +2
This paper addresses the problem of determining dense pixel correspondences between two images and its application to geometric correspondence verification in image retrieval. The…
Multi-View Stereo by Temporal Nonparametric Fusion
Yuxin Hou, Juho Kannala, Arno Solin
We propose a novel idea for depth estimation from multi-view image-pose pairs, where the model has capability to leverage information from previous latent-space encodings of the sc…
Towards Photographic Image Manipulation with Balanced Growing of Generative Autoencoders
Ari Heljakka, Arno Solin, Juho Kannala
We present a generative autoencoder that provides fast encoding, faithful reconstructions (eg. retaining the identity of a face), sharp generated/reconstructed samples in high reso…
ICface: Interpretable and Controllable Face Reenactment Using GANs
Soumya Tripathy, Juho Kannala, Esa Rahtu
This paper presents a generic face animator that is able to control the pose and expressions of a given face image. The animation is driven by human interpretable control signals c…
Regularizing Trajectory Optimization with Denoising Autoencoders
Rinu Boney, Norman Di Palo, Mathias Berglund +4
Trajectory optimization using a learned model of the environment is one of the core elements of model-based reinforcement learning. This procedure often suffers from exploiting ina…
Interpolation Consistency Training for Semi-Supervised Learning
Vikas Verma, Kenji Kawaguchi, Alex Lamb +4
We introduce Interpolation Consistency Training (ICT), a simple and computation efficient algorithm for training Deep Neural Networks in the semi-supervised learning paradigm. ICT…
Unstructured Multi-View Depth Estimation Using Mask-Based Multiplane Representation
Yuxin Hou, Arno Solin, Juho Kannala
This paper presents a novel method, MaskMVS, to solve depth estimation for unstructured multi-view image-pose pairs. In the plane-sweep procedure, the depth planes are sampled by h…
Mask-RCNN and U-net Ensembled for Nuclei Segmentation
Aarno Oskar Vuola, Saad Ullah Akram, Juho Kannala
Nuclei segmentation is both an important and in some ways ideal task for modern computer vision methods, e.g. convolutional neural networks. While recent developments in theory and…
Semantic Matching by Weakly Supervised 2D Point Set Registration
Zakaria Laskar, Hamed R. Tavakoli, Juho Kannala
In this paper we address the problem of establishing correspondences between different instances of the same object. The problem is posed as finding the geometric transformation th…
Semi-Supervised Semantic Matching
Zakaria Laskar, Juho Kannala
Convolutional neural networks (CNNs) have been successfully applied to solve the problem of correspondence estimation between semantically related images. Due to non-availability o…