Budvytis, I.[Ignas]
* 2010: Label propagation in complex video sequences using semi-supervised learning
* 2010: Making a Shallow Network Deep: Growing a Tree from Decision Regions of a Boosting Classifier
* 2011: Semi-Supervised Video Segmentation Using Tree Structured Graphical Models
* 2012: Making a Shallow Network Deep: Conversion of a Boosting Classifier into a Decision Tree by Boolean Optimisation
* 2012: MoT: Mixture of Trees Probabilistic Graphical Model for Video Segmentation
* 2013: Semi-Supervised Video Segmentation Using Tree Structured Graphical Models
* 2014: Mixture of Trees Probabilistic Graphical Model for Video Segmentation
* 2017: Large Scale Labelled Video Data Augmentation for Semantic Segmentation in Driving Scenarios
* 2020: Efficient Large-scale Semantic Visual Localization in 2d Maps
* 2020: Rotation Equivariant Orientation Estimation for Omnidirectional Localization
* 2021: Estimating and Exploiting the Aleatoric Uncertainty in Surface Normal Estimation
* 2021: Hierarchical Kinematic Probability Distributions for 3D Human Shape and Pose Estimation from Images in the Wild
* 2021: Lifted Semantic Graph Embedding for Omnidirectional Place Recognition
* 2021: Probabilistic 3D Human Shape and Pose Estimation from Multiple Unconstrained Images in the Wild
* 2021: PX-NET: Simple and Efficient Pixel-Wise Training of Photometric Stereo Networks
* 2022: Efficient Large-scale Localization by Global Instance Recognition
* 2022: Multi-View Depth Estimation by Fusing Single-View Depth Probability with Multi-View Geometry
* 2023: CNN Based Approach for the Point-Light Photometric Stereo Problem, A
* 2023: HuManiFlow: Ancestor-Conditioned Normalising Flows on SO(3) Manifolds for Human Pose and Shape Distribution Estimation
* 2023: IMP: Iterative Matching and Pose Estimation with Adaptive Pooling
* 2023: SFD2: Semantic-Guided Feature Detection and Description
* 2024: Neural Height-Map Approach for the Binocular Photometric Stereo Problem, A
Includes: Budvytis, I.[Ignas] Budvytis, I.
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