Search Results for author:
Found 9 papers, 7 papers with code
Expansion of Visual Hints for Improved Generalization in Stereo Matching
We introduce visual hints expansion for guiding stereo matching to improve generalization.
Novel View Synthesis via Depth-guided Skip Connections
Flow predictions enable the target view to re-use pixels directly, but can easily lead to distorted results.
Learning Attribute-Driven Disentangled Representations for Interactive Fashion Retrieval
Interactive retrieval for online fashion shopping provides the ability of changing image retrieval results according to the user feedback.
Movement-induced Priors for Deep Stereo
We propose a method for fusing stereo disparity estimation with movement-induced prior information.
Deep Automodulators
These networks can faithfully reproduce individual real-world input images like regular autoencoders, but also generate a fused sample from an arbitrary combination of several such images, allowing instantaneous 'style-mixing' and other new applications.
Gaussian Process Priors for View-Aware Inference
While frame-independent predictions with deep neural networks have become the prominent solutions to many computer vision tasks, the potential benefits of utilizing correlations between frames have received less attention.
Iterative Path Reconstruction for Large-Scale Inertial Navigation on Smartphones
Modern smartphones have all the sensing capabilities required for accurate and robust navigation and tracking.
Multi-View Stereo by Temporal Nonparametric Fusion
The flexibility of the Gaussian process (GP) prior provides adapting memory for fusing information from previous views.
Unstructured Multi-View Depth Estimation Using Mask-Based Multiplane Representation
This paper presents a novel method, MaskMVS, to solve depth estimation for unstructured multi-view image-pose pairs.
