8 papers
Expansion of Visual Hints for Improved Generalization in Stereo Matching
Andrea Pilzer, Yuxin Hou, Niki Loppi +2
We introduce visual hints expansion for guiding stereo matching to improve generalization. Our work is motivated by the robustness of Visual Inertial Odometry (VIO) in computer vis…
Novel View Synthesis via Depth-guided Skip Connections
Yuxin Hou, Arno Solin, Juho Kannala
We introduce a principled approach for synthesizing new views of a scene given a single source image. Previous methods for novel view synthesis can be divided into image-based rend…
Movement-induced Priors for Deep Stereo
Yuxin Hou, Muhammad Kamran Janjua, Juho Kannala +1
We propose a method for fusing stereo disparity estimation with movement-induced prior information. Instead of independent inference frame-by-frame, we formulate the problem as a n…
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,…
Gaussian Process Priors for View-Aware Inference
Yuxin Hou, Ari Heljakka, Arno Solin
While frame-independent predictions with deep neural networks have become the prominent solutions to many computer vision tasks, the potential benefits of utilizing correlations be…
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…