mlsanityData to 14 Oct 2026

CIGLI: Conditional Image Generation from Language & Image

arXiv 2108.08955 ↗First posted 20 Aug 2021cs.CV cs.CLcited by 3

Not on the map. Why?

Abstract (arXiv)

Multi-modal generation has been widely explored in recent years. Current research directions involve generating text based on an image or vice versa. In this paper, we propose a new task called CIGLI: Conditional Image Generation from Language and Image. Instead of generating an image based on text as in text-image generation, this task requires the generation of an image from a textual description and an image prompt. We designed a new dataset to ensure that the text description describes information from both images, and that solely analyzing the description is insufficient to generate an image. We then propose a novel language-image fusion model which improves the performance over two established baseline methods, as evaluated by quantitative (automatic) and qualitative (human) evaluations. The code and dataset is available at https://github.com/vincentlux/CIGLI.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 14 of its 20 references that are in the map. First posted on arXiv 20 Aug 2021.

Builds on

14 of 20 references.

References · 14

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2014Microsoft COCO: Common Objects in Contextcited by 17,608
  3. 2021Zero-Shot Text-to-Image Generationcited by 4,288
  4. 2016Improved Techniques for Training GANscited by 2,970
  5. 2019LXMERT: Learning Cross-Modality Encoder Representations from Transformerscited by 1,553
  6. 2019VL-BERT: Pre-training of Generic Visual-Linguistic Representationscited by 954
  7. 2016Generative Adversarial Text to Image Synthesiscited by 735
  8. 2017AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networkscited by 664
  9. 2016StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networkscited by 577
  10. 2018A Corpus for Reasoning About Natural Language Grounded in Photographscited by 459
  11. 2015DRAW: A Recurrent Neural Network For Image Generationcited by 191
  12. 2016Learning What and Where to Drawcited by 105
2 more
  1. 2017A Generative Adversarial Approach for Zero-Shot Learning from Noisy Textscited by 96
  2. 2020X-LXMERT: Paint, Caption and Answer Questions with Multi-Modal Transformerscited by 59

Built on by

Cited by year

Citing papers per year: 2021: 1; 2022: 0; 2023: 0; 2024: 1; 2025: 1.

3 papers.

  1. 2021TraVLR: Now You See It, Now You Don't! A Bimodal Dataset for Evaluating Visio-Linguistic Reasoningcited by 4
  2. 2024Robust Disaster Assessment from Aerial Imagery Using Text-to-Image Synthetic Datacited by 4
  3. 2025SegSub: Evaluating Robustness to Knowledge Conflicts and Hallucinations in Vision-Language Modelscited by 2