Papers Handwriting generation
“Handwriting generation” 태그가 달린 논문 20편 · 필터 해제
WriteViT: Handwritten Text Generation with Vision Transformer
Humans can quickly generalize handwriting styles from a single example by intuitively separating content from style. Machines, however, struggle with this task, especially in low-data settings, often missing subtle spati…
Handwriting generationText GenerationCost-Effective Robotic Handwriting System with AI Integration
This paper introduces a cost-effective robotic handwriting system designed to replicate human-like handwriting with high precision. Combining a Raspberry Pi Pico microcontroller, 3D-printed components, and a machine lear…
Handwriting generationPICODecoupling Layout from Glyph in Online Chinese Handwriting Generation
Text plays a crucial role in the transmission of human civilization, and teaching machines to generate online handwritten text in various styles presents an interesting and significant challenge. However, most prior work…
Handwriting generationOne-Shot Diffusion Mimicker for Handwritten Text Generation
Existing handwritten text generation methods often require more than ten handwriting samples as style references. However, in practical applications, users tend to prefer a handwriting generation model that operates with…
Handwriting generationText GenerationRethinking HTG Evaluation: Bridging Generation and Recognition
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 Handwriting Generation, even if they might no…
DiversityHandwriting generationHTRStatic and Dynamic Synthesis of Bengali and Devanagari Signatures
Developing an automatic signature verification system is challenging and demands a large number of training samples. This is why synthetic handwriting generation is an emerging topic in document image analysis. Some hand…
Handwriting generationData Generation for Post-OCR correction of Cyrillic handwriting
This paper introduces a novel approach to post-Optical Character Recognition Correction (POC) for handwritten Cyrillic text, addressing a significant gap in current research methodologies. This gap is due to the lack of …
Handwriting generationHandwritten Text RecognitionHTROptical Character Recognition+2Sampling and Ranking for Digital Ink Generation on a tight computational budget
Digital ink (online handwriting) generation has a number of potential applications for creating user-visible content, such as handwriting autocompletion, spelling correction, and beautification. Writing is personal and u…
Handwriting generationSpelling CorrectionWordStylist: Styled Verbatim Handwritten Text Generation with Latent Diffusion Models
Text-to-Image synthesis is the task of generating an image according to a specific text description. Generative Adversarial Networks have been considered the standard method for image synthesis virtually since their intr…
Data AugmentationDenoisingHandwriting generationHTR+4Disentangling Writer and Character Styles for Handwriting Generation
Training machines to synthesize diverse handwritings is an intriguing task. Recently, RNN-based methods have been proposed to generate stylized online Chinese characters. However, these methods mainly focus on capturing …
Handwriting generationDiffusion models for Handwriting Generation
In this paper, we propose a diffusion probabilistic model for handwriting generation. Diffusion models are a class of generative models where samples start from Gaussian noise and are gradually denoised to produce output…
Handwriting generationWhat is the Reward for Handwriting? -- Handwriting Generation by Imitation Learning
Analyzing the handwriting generation process is an important issue and has been tackled by various generation models, such as kinematics based models and stochastic models. In this study, we use a reinforcement learning …
Handwriting generationImitation LearningReinforcement Learning (RL)DeepWriteSYN: On-Line Handwriting Synthesis via Deep Short-Term Representations
This study proposes DeepWriteSYN, a novel on-line handwriting synthesis approach via deep short-term representations. It comprises two modules: i) an optional and interchangeable temporal segmentation, which divides the …
Handwriting generationOne-Shot LearningText and Style Conditioned GAN for Generation of Offline Handwriting Lines
This paper presents a GAN for generating images of handwritten lines conditioned on arbitrary text and latent style vectors. Unlike prior work, which produce stroke points or single-word images, this model generates enti…
Handwriting generationDeep imitator: Handwriting calligraphy imitation via deep attention networks
Calligraphy imitation (CI) from a handful of target handwriting samples is such a challenging task that most of the existing writing style analysis or handwriting generation methods do not exhibit satisfactory performanc…
Deep AttentionHandwriting generationScrabbleGAN: Semi-Supervised Varying Length Handwritten Text Generation
Optical character recognition (OCR) systems performance have improved significantly in the deep learning era. This is especially true for handwritten text recognition (HTR), where each author has a unique style, unlike p…
Domain AdaptationHandwriting generationHandwriting RecognitionHandwritten Text Recognition+4Handwriting styles: benchmarks and evaluation metrics
Evaluating the style of handwriting generation is a challenging problem, since it is not well defined. It is a key component in order to develop in developing systems with more personalized experiences with humans. In th…
Handwriting generationTemporal SequencesDeepWriting: Making Digital Ink Editable via Deep Generative Modeling
Digital ink promises to combine the flexibility and aesthetics of handwriting and the ability to process, search and edit digital text. Character recognition converts handwritten text into a digital representation, albei…
Handwriting generationHandwritten Word GenerationStyle TransferProfessor Forcing: A New Algorithm for Training Recurrent Networks
The Teacher Forcing algorithm trains recurrent networks by supplying observed sequence values as inputs during training and using the network's own one-step-ahead predictions to do multi-step sampling. We introduce the P…
Domain AdaptationHandwriting generationImage GenerationLanguage Modeling+1HyperNetworks
This work explores hypernetworks: an approach of using a one network, also known as a hypernetwork, to generate the weights for another network. Hypernetworks provide an abstraction that is similar to what is found in na…
Handwriting generationLanguage ModellingMachine TranslationTranslation