Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 15 of 15 for “"Text-to-image Generation"”.
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Glass onion: Compositional text-to-image generation using diffusion models and LLMs
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-02-04 without embargo terms
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Social stereotypes in text-to-image generation: Examining user perceptions and debiasing strategies
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01
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Multi-Subject Image Generation
Diffusion models excel at text-to-image generation, especially in subject-driven generation for personalized images. However, existing methods are inefficient due to the subject-specific fine-tuning, which is computationally intensive and hampers efficient deployment. Moreover, existing methods …
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Constructing three-dimensional virtual spaces with the application of artificial intelligence
… It evaluates a five-stage workflow combining text-to-image generation, image-to-3D reconstruction using Tencent Hunyuan3D 2.0, and manual optimization in Blender. The workflow was applied to architectural and sculptural landmarks to test rendering performance on a Meta Quest 3 headset. Results …
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Data-Efficient Bilingual Lexicon Induction with Pretrained Language Models
… data-efficient BLI approaches aimed at automatically inducing high-quality bilingual dictionaries in low-data scenarios, thereby bridging the lexical gaps between languages. While previous BLI methods rely on mapping static word embeddings, inspired by the paradigm shifts towards …
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Concepts from unclear textual embeddings for text-to-image synthesis
Automatically generating images based on a natural language description is a challenging problem with several key applications in the fields of retail, marketing, education and entertainment. In the last few years, some progress has been made in this direction specifically by using Generative …
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Uncertainty-Inclusive Contrastive Learning for Leveraging Synthetic Images
Recent advancements in text-to-image generation models have sparked a growing interest in using synthesized training data to improve few-shot learning performance. Prevailing approaches treat all generated data as uniformly important, neglecting the fact that the quality of generated images varies …
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Leveraging the Latent Space for Model Understanding and Optimization
… performance on tasks such as classification or image generation. However, these models are typically limited by two key factors. First, models such as those used in tasks of text-to-image generation lack interpretation. Second, models that leverage the latent space to represent data struggle to …
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Learning Low-Level Priors from Images for Inference and Synthesis
… critical for both downstream applications and photorealistic synthesis. Tasks such as image classification, semantic segmentation, and text-to-image generation parse the scene in terms of high-level properties of objects and scene. Along with understanding and creating visual media along these …
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Imagine Yourself: Explorations in Fostering Personal Expression with Generative AI
… has been promoted with many exciting promises to enhance human creativity. However, it has also been shown to amplify human bias and perpetuate harmful stereotypes. In the new age being ushered in by this technology, this thesis explores how educators and designers can use this technology to …
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Towards a Unified Framework for Visual Recognition and Generation via Masked Generative Modeling
Recognition and generation are two key tasks in computer vision. However, recognition and generative models are typically trained independently, which ignores the complementary nature of the two tasks. In this thesis, we present a unified framework for visual data recognition and generation via …
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Learning 3D Robotics Perception using Inductive Priors
Recent advances in deep learning have led to a data-centric intelligence in the last decade, i.e. artificially intelligent models unlocking the potential to ingest a large amount of data and be really good at performing digital tasks such as text-to-image generation, machine-human conversation, and …
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Discovering and Personalizing Artistic Styles with Generative Models
Text-to-image models have gained widespread popularity, transforming digital art creation by allowing users to generate highly detailed and imaginative visual content from natural language prompts. These models are now widely adopted across various domains, particularly in the arts, where they …
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Principled Methods for Advancing Generative Machine Learning
… vision (CV), diffusion models mark a major milestone — they can synthesize photo-realistic and diverse images, outperforming previous state-of-the-art approaches such as generative adversarial networks (GANs). In computer graphics, Gaussian splatting achieves high-fidelity novel view synthesis, …
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Reasoning, scaling, generating with vision-language models
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-09-16 without embargo terms