mlsanityData to 14 Oct 2026

A Survey of AI Text-to-Image and AI Text-to-Video Generators

arXiv 2311.06329 ↗First posted 10 Nov 2023cs.CV cs.AI cs.CLcited by 17

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Abstract (arXiv)

Text-to-Image and Text-to-Video AI generation models are revolutionary technologies that use deep learning and natural language processing (NLP) techniques to create images and videos from textual descriptions. This paper investigates cutting-edge approaches in the discipline of Text-to-Image and Text-to-Video AI generations. The survey provides an overview of the existing literature as well as an analysis of the approaches used in various studies. It covers data preprocessing techniques, neural network types, and evaluation metrics used in the field. In addition, the paper discusses the challenges and limitations of Text-to-Image and Text-to-Video AI generations, as well as future research directions. Overall, these models have promising potential for a wide range of applications such as video production, content creation, and digital marketing.

Key facts. Cited by 17 papers in the map (data through 14 Oct 2026). Builds on 16 of its 21 references that are in the map. First posted on arXiv 10 Nov 2023.

Builds on

16 of 21 references.

References · 16

  1. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,585
  2. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,355
  3. 2022Imagen Video: High Definition Video Generation with Diffusion Modelscited by 1,778
  4. 2022Make-A-Video: Text-to-Video Generation without Text-Video Datacited by 1,742
  5. 2022CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformerscited by 985
  6. 2016Generative Adversarial Text to Image Synthesiscited by 735
  7. 2021CogView: Mastering Text-to-Image Generation via Transformerscited by 694
  8. 2023Muse: Text-To-Image Generation via Masked Generative Transformerscited by 648
  9. 2022Phenaki: Variable Length Video Generation From Open Domain Textual Descriptioncited by 484
  10. 2021Multimodal datasets: misogyny, pornography, and malignant stereotypescited by 327
  11. 2022CogView2: Faster and Better Text-to-Image Generation via Hierarchical Transformerscited by 307
  12. 2021GODIVA: Generating Open-DomaIn Videos from nAtural Descriptionscited by 256
4 more
  1. 2021N"UWA: Visual Synthesis Pre-training for Neural visUal World creAtioncited by 253
  2. 2019Identifying and Reducing Gender Bias in Word-Level Language Modelscited by 214
  3. 2021Understanding and Creating Art with AI: Review and Outlookcited by 60
  4. 2020Text-to-Image Generation with Attention Based Recurrent Neural Networkscited by 2

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 4; 2025: 9; 2026: 4.

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  1. 2025Agentic Retrieval-Augmented Generation: A Survey on Agentic RAGcited by 249
  2. 2024Sora as a World Model? A Complete Survey on Text-to-Video Generationcited by 53
  3. 2024A Survey on Generative AI and LLM for Video Generation, Understanding, and Streamingcited by 37
  4. 2024A Survey of Sustainability in Large Language Models: Applications, Economics, and Challengescited by 18
  5. 2025Simulating the Real World: A Unified Survey of Multimodal Generative Modelscited by 15
  6. 2025LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretationcited by 10
  7. 2024Exploring Prompt Engineering: A Systematic Review with SWOT Analysiscited by 5
  8. 2025A Survey: Spatiotemporal Consistency in Video Generationcited by 3
  9. 2025Bridging Text and Video Generation: A Surveycited by 2
  10. 2025Compliance Rating Scheme: A Data Provenance Framework for Generative AI Datasetscited by 2
  11. 2025Foundations of GenIRcited by 1
  12. 2025SSG-Dit: A Spatial Signal Guided Framework for Controllable Video Generationcited by 1
5 more
  1. 2025Zero-Shot Visual Deepfake Detection: Can AI Predict and Prevent Fake Content Before It's Created?cited by 1
  2. 2026Process-of-Thought Reasoning for Videoscited by 1
  3. 2026SKeDA: A Generative Watermarking Framework for Text-to-video Diffusion Modelscited by 1
  4. 2026Are Video Generation Models Geographically Fair? An Attraction-Centric Evaluation of Global Visual Knowledgecited by 0
  5. 2026Polaris: Scaling Up Instruction-Guided Image Generation Towards Millions of Personalized Style Needscited by 0