research
∙
03/13/2023
Collision Cross-entropy and EM Algorithm for Self-labeled Classification
We propose "collision cross-entropy" as a robust alternative to the Shan...
share
research
∙
01/26/2023
Revisiting Discriminative Entropy Clustering and its relation to K-means
Maximization of mutual information between the model's input and output ...
research
∙
04/05/2021
Robust Trust Region for Weakly Supervised Segmentation
Acquisition of training data for the standard semantic segmentation is e...
research
∙
03/26/2021
Confluent Vessel Trees with Accurate Bifurcations
We are interested in unsupervised reconstruction of complex near-capilla...
research
∙
02/10/2020
RePose: Learning Deep Kinematic Priors for Fast Human Pose Estimation
We propose a novel efficient and lightweight model for human pose estima...
research
∙
01/15/2020
Image Segmentation Using Deep Learning: A Survey
Image segmentation is a key topic in image processing and computer visio...
research
∙
07/16/2019
Efficient Segmentation: Learning Downsampling Near Semantic Boundaries
Many automated processes such as auto-piloting rely on a good semantic s...
research
∙
11/24/2018
Divergence Prior and Vessel-tree Reconstruction
We propose a new geometric regularization principle for reconstructing v...
research
∙
09/07/2018
ADM for grid CRF loss in CNN segmentation
Variants of gradient descent (GD) dominate CNN loss minimization in comp...
research
∙
05/12/2018
Constrained-CNN losses forweakly supervised segmentation
Weak supervision, e.g., in the form of partial labels or image tags, is ...
research
∙
04/04/2018
Normalized Cut Loss for Weakly-supervised CNN Segmentation
Most recent semantic segmentation methods train deep convolutional neura...
research
∙
03/26/2018
On Regularized Losses for Weakly-supervised CNN Segmentation
Minimization of regularized losses is a principled approach to weak supe...
research
∙
05/16/2017
Kernel clustering: density biases and solutions
Kernel methods are popular in clustering due to their generality and dis...
research
∙
03/30/2017
Efficient optimization for Hierarchically-structured Interacting Segments (HINTS)
We propose an effective optimization algorithm for a general hierarchica...
research
∙
02/02/2016
A-expansion for multiple "hedgehog" shapes
Overlapping colors and cluttered or weak edges are common segmentation p...
research
∙
06/24/2015
Kernel Cuts: MRF meets Kernel & Spectral Clustering
We propose a new segmentation model combining common regularization ener...
research
∙
06/15/2015
Thin Structure Estimation with Curvature Regularization
Many applications in vision require estimation of thin structures such a...
research
∙
05/01/2015
Volumetric Bias in Segmentation and Reconstruction: Secrets and Solutions
Many standard optimization methods for segmentation and reconstruction c...
research
∙
07/23/2014
Joint Energy-based Detection and Classificationon of Multilingual Text Lines
This paper proposes a new hierarchical MDL-based model for a joint detec...
research
∙
11/08/2013
An Experimental Comparison of Trust Region and Level Sets
High-order (non-linear) functionals have become very popular in segmenta...
research
∙
11/08/2013
Submodularization for Quadratic Pseudo-Boolean Optimization
Many computer vision problems require optimization of binary non-submodu...
research
∙
11/07/2013
