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Found 17 papers, 6 papers with code
VATr++: Choose Your Words Wisely for Handwritten Text Generation
Styled Handwritten Text Generation (HTG) has received significant attention in recent years, propelled by the success of learning-based solutions employing GANs, Transformers, and, preliminarily, Diffusion Models.
HWD: A Novel Evaluation Score for Styled Handwritten Text Generation
Through extensive experimental evaluation on different word-level and line-level datasets of handwritten text images, we demonstrate the suitability of the proposed HWD as a score for Styled HTG.
Volumetric Fast Fourier Convolution for Detecting Ink on the Carbonized Herculaneum Papyri
Recent advancements in Digital Document Restoration (DDR) have led to significant breakthroughs in analyzing highly damaged written artifacts.
How to Choose Pretrained Handwriting Recognition Models for Single Writer Fine-Tuning
Recent advancements in Deep Learning-based Handwritten Text Recognition (HTR) have led to models with remarkable performance on both modern and historical manuscripts in large benchmark datasets.
Evaluating Synthetic Pre-Training for Handwriting Processing Tasks
In this work, we explore massive pre-training on synthetic word images for enhancing the performance on four benchmark downstream handwriting analysis tasks.
Handwritten Text Generation from Visual Archetypes
Generating synthetic images of handwritten text in a writer-specific style is a challenging task, especially in the case of unseen styles and new words, and even more when these latter contain characters that are rarely encountered during training.
Embodied Agents for Efficient Exploration and Smart Scene Description
The development of embodied agents that can communicate with humans in natural language has gained increasing interest over the last years, as it facilitates the diffusion of robotic platforms in human-populated environments.
Boosting Modern and Historical Handwritten Text Recognition with Deformable Convolutions
Handwritten Text Recognition (HTR) in free-layout pages is a challenging image understanding task that can provide a relevant boost to the digitization of handwritten documents and reuse of their content.
The LAM Dataset: A Novel Benchmark for Line-Level Handwritten Text Recognition
With the aim of fostering the research on this topic, in this paper we present the Ludovico Antonio Muratori (LAM) dataset, a large line-level HTR dataset of Italian ancient manuscripts edited by a single author over 60 years.
Embodied Navigation at the Art Gallery
This feature is challenging for occupancy-based agents which are usually trained in crowded domestic environments with plenty of occupancy information.
Spot the Difference: A Novel Task for Embodied Agents in Changing Environments
To make a step towards this setting, we propose Spot the Difference: a novel task for Embodied AI where the agent has access to an outdated map of the environment and needs to recover the correct layout in a fixed time budget.
CaMEL: Mean Teacher Learning for Image Captioning
Describing images in natural language is a fundamental step towards the automatic modeling of connections between the visual and textual modalities.
Focus on Impact: Indoor Exploration with Intrinsic Motivation
The proposed exploration approach outperforms DRL-based competitors relying on intrinsic rewards and surpasses the agents trained with a dense extrinsic reward computed with the environment layouts.
From Show to Tell: A Survey on Deep Learning-based Image Captioning
Starting from 2015 the task has generally been addressed with pipelines composed of a visual encoder and a language model for text generation.
Out of the Box: Embodied Navigation in the Real World
In this work, we detail how to transfer the knowledge acquired in simulation into the real world.
The Role of the Input in Natural Language Video Description
Natural Language Video Description (NLVD) has recently received strong interest in the Computer Vision, Natural Language Processing (NLP), Multimedia, and Autonomous Robotics communities.
Explore and Explain: Self-supervised Navigation and Recounting
In this paper, we devise a novel embodied setting in which an agent needs to explore a previously unknown environment while recounting what it sees during the path.
