Text-to-Image Synthesis: A Decade Survey

arXiv:2411.16164 · cs.CV · Submitted 2024-11-25 · Read on arXiv

cs.CV

Submitted: 2024-11-25

Updated: 2026-10-15

Comments: In this survey, we review over 490 recent works on T2I

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Diffusion Model — 145× in this paper · explained in 9 episodes
• Diffusion Models — 107× in this paper · explained in 8 episodes
• Consistency — 57× in this paper · explained in 3 episodes
• Transformer — 41× in this paper · explained in 2 episodes
• Fidelity — 27× in this paper · explained in 2 episodes
• Fine-Tuning — 27× in this paper · explained in 5 episodes
• Accuracy — 24× in this paper · explained in 1 episode
• Generator — 21× in this paper · explained in 2 episodes
• Generative Model — 18× in this paper · explained in 2 episodes
• Embeddings — 17× in this paper · explained in 2 episodes
• Personalization — 16× in this paper · explained in 2 episodes
• Generative Models — 15× in this paper · explained in 3 episodes
• Attention Mechanism — 13× in this paper · explained in 3 episodes
• Contrastive Learning — 13× in this paper · explained in 7 episodes
• Distillation — 13× in this paper · explained in 2 episodes
• Transformers — 13× in this paper · explained in 2 episodes
• Data Augmentation — 10× in this paper · explained in 7 episodes
• Generative Adversarial Networks — 10× in this paper
• Benchmark — 9× in this paper · explained in 2 episodes
• Diffusion Process — 8× in this paper · explained in 2 episodes
• Adaptation — 7× in this paper · explained in 1 episode
• Latent Space — 7× in this paper · explained in 7 episodes
• Reinforcement Learning — 7× in this paper · explained in 4 episodes
• Transformer Architecture — 6× in this paper · explained in 3 episodes
• Decoder — 5× in this paper · explained in 2 episodes
• Papers — 5× in this paper · explained in 3 episodes
• Regularization — 5× in this paper · explained in 3 episodes
• Robustness — 5× in this paper · explained in 5 episodes
• Adversarial Examples — 4× in this paper · explained in 2 episodes
• Coherence — 4× in this paper · explained in 2 episodes
• Generative AI — 4× in this paper · explained in 2 episodes
• Multimodal Learning — 4× in this paper · explained in 2 episodes
• Quantization — 4× in this paper · explained in 13 episodes
• Unified Framework — 4× in this paper · explained in 5 episodes
• Adversarial Diffusion Distillation — 3× in this paper
• Clustering — 3× in this paper · explained in 2 episodes
• Core — 3× in this paper · explained in 2 episodes
• Cross-Attention Mechanism — 3× in this paper · explained in 2 episodes
• Diffusion Processes — 3× in this paper · explained in 2 episodes
• Foundation Model — 3× in this paper · explained in 3 episodes
• Grounding — 3× in this paper · explained in 3 episodes
• Human Feedback Inversion — 3× in this paper
• Large Language Models (LLMs) — 3× in this paper · explained in 8 episodes
• Latent Diffusion Model — 3× in this paper · explained in 2 episodes
• Mutual Information — 3× in this paper · explained in 2 episodes
• Semantic Preservation — 3× in this paper · explained in 2 episodes
• Semantic Understanding — 3× in this paper · explained in 2 episodes
• Speculative Jacobi Decoding — 3× in this paper
• Visual Question Answering — 3× in this paper
• ACM Transactions on Graphics — 2× in this paper
• Adversarial Training — 2× in this paper · explained in 1 episode
• Artificial Intelligence Generated Content — 2× in this paper
• Benchmarking — 2× in this paper · explained in 4 episodes
• Contextual Understanding — 2× in this paper · explained in 3 episodes
• Cosine Similarity — 2× in this paper · explained in 3 episodes
• Denoising Diffusion Probabilistic Models — 2× in this paper
• Emotional Image Content Generation — 2× in this paper
• Feature Extraction — 2× in this paper · explained in 3 episodes
• Foundation Models — 2× in this paper · explained in 7 episodes
• Human Preference Score — 2× in this paper
• Hybrid Approach — 2× in this paper · explained in 4 episodes
• Hypernetwork — 2× in this paper · explained in 3 episodes
• Instruction Tuning — 2× in this paper · explained in 3 episodes
• K-means Clustering — 2× in this paper · explained in 2 episodes
• Loss Function — 2× in this paper · explained in 2 episodes
• Planner — 2× in this paper · explained in 2 episodes
• Prompt Engineering — 2× in this paper · explained in 5 episodes
• Reward Function — 2× in this paper · explained in 3 episodes
• Semantic Alignment — 2× in this paper · explained in 4 episodes
• Semantic Object Accuracy — 2× in this paper
• Visual Commonsense Reasoning — 2× in this paper
• Accountability — 1× in this paper · explained in 2 episodes
• Activation Function — 1× in this paper · explained in 1 episode
• Active Learning — 1× in this paper · explained in 6 episodes
• Adaptability — 1× in this paper · explained in 1 episode
• Adaptive Selection — 1× in this paper · explained in 1 episode
• Adversarial Attacks — 1× in this paper · explained in 1 episode
• Annealed Importance Guidance — 1× in this paper
• Artificial Intelligence (AI) — 1× in this paper · explained in 2 episodes
• Calibration — 1× in this paper · explained in 7 episodes
• Chain-of-Thought Prompting — 1× in this paper · explained in 2 episodes
• Computational overhead — 1× in this paper · explained in 2 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Edge Devices — 1× in this paper · explained in 2 episodes
• Entanglement — 1× in this paper · explained in 4 episodes
• Evaluation Framework — 1× in this paper · explained in 2 episodes
• Frechet Inception Distance — 1× in this paper
• Generalization — 1× in this paper · explained in 13 episodes
• Holistic Evaluation of Text-to-Image Models — 1× in this paper
• Image Generative Pre-trained Transformer — 1× in this paper
• In-Context Learning — 1× in this paper · explained in 7 episodes
• Inception Score — 1× in this paper
• Kernel Inception Distance — 1× in this paper
• Kernel Precision Recall — 1× in this paper
• Knowledge Distillation — 1× in this paper · explained in 12 episodes
• Latent Diffusion Models — 1× in this paper · explained in 2 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Low-Rank Adaptation (LoRA) — 1× in this paper · explained in 11 episodes
• MLLMs — 1× in this paper · explained in 2 episodes
• Memorization — 1× in this paper · explained in 2 episodes

Sources

• Generating Images from Captions with Attention
• GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models
• Hierarchical Text-Conditional Image Generation with CLIP Latents
• SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis
• CogView3: Finer and Faster Text-to-Image Generation via Relay Diffusion
• Language Models are Few-Shot Learners
• An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
• AI-Generated Content (AIGC): A Survey
• Emu: Enhancing Image Generation Models Using Photogenic Needles in a Haystack
• Scaling Autoregressive Multi-Modal Models: Pretraining and Instruction Tuning
• MARS: Mixture of Auto-Regressive Models for Fine-grained Text-to-image Synthesis
• PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis
• Conditional Generative Adversarial Nets
• Text-to-image Diffusion Models in Generative AI: A Survey
• Controllable Generation with Text-to-Image Diffusion Models: A Survey
• Auto-Encoding Variational Bayes
• Discrete Variational Autoencoders
• SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing
• Classifier-Free Diffusion Guidance
• TAC-GAN - Text Conditioned Auxiliary Classifier Generative Adversarial Network

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