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20152024
most citedA Comprehensive guide to Bayesian Convolutional Neural Network with Variational Inference

162 citations · 471 across the 24 of their papers we have counts for

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22 papers · 1 filter

cs.CV2024

DiffusionPen: Towards Controlling the Style of Handwritten Text Generation

Konstantina Nikolaidou, George Retsinas, Giorgos Sfikas +1

Handwritten Text Generation (HTG) conditioned on text and style is a challenging task due to the variability of inter-user characteristics and the unlimited combinations of charact…

cs.CV2024

Rethinking HTG Evaluation: Bridging Generation and Recognition

Konstantina Nikolaidou, George Retsinas, Giorgos Sfikas +1

The evaluation of generative models for natural image tasks has been extensively studied. Similar protocols and metrics are used in cases with unique particularities, such as Handw…

cs.CV2022

Depth Contrast: Self-Supervised Pretraining on 3DPM Images for Mining Material Classification

Prakash Chandra Chhipa, Richa Upadhyay, Rajkumar Saini +4

This work presents a novel self-supervised representation learning method to learn efficient representations without labels on images from a 3DPM sensor (3-Dimensional Particle Mea…

cs.CV20221 cited

Deep Neural Network approaches for Analysing Videos of Music Performances

Foteini Simistira Liwicki, Richa Upadhyay, Prakash Chandra Chhipa +4

This paper presents a framework to automate the labelling process for gestures in musical performance videos with a 3D Convolutional Neural Network (CNN). While this idea was propo…

cs.CV2021

Current Status and Performance Analysis of Table Recognition in Document Images with Deep Neural Networks

Khurram Azeem Hashmi, Marcus Liwicki, Didier Stricker +3

The first phase of table recognition is to detect the tabular area in a document. Subsequently, the tabular structures are recognized in the second phase in order to extract inform…

cs.CV2021

Guided Table Structure Recognition through Anchor Optimization

Khurram Azeem Hashmi, Didier Stricker, Marcus Liwicki +2

This paper presents the novel approach towards table structure recognition by leveraging the guided anchors. The concept differs from current state-of-the-art approaches for table…