# Sequential Attention GAN for Interactive Image Editing

arXiv: https://arxiv.org/abs/1812.08352 · HTML: https://mlsanity.com/paper/1812.08352/

## Key facts

- Cited by 33 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Dec 2018.

## Built on by (most cited first, 30 of 33)

- [ImgEdit: A Unified Image Editing Dataset and Benchmark](https://mlsanity.com/paper/2505.20275/) (2025)
- [Talk-to-Edit: Fine-Grained Facial Editing via Dialog](https://mlsanity.com/paper/2109.04425/) (2021)
- [EnvEdit: Environment Editing for Vision-and-Language Navigation](https://mlsanity.com/paper/2203.15685/) (2022)
- [Adversarial Text-to-Image Synthesis: A Review](https://mlsanity.com/paper/2101.09983/) (2021)
- [Improving Generation and Evaluation of Visual Stories via Semantic Consistency](https://mlsanity.com/paper/2105.10026/) (2021)
- [Learning by Planning: Language-Guided Global Image Editing](https://mlsanity.com/paper/2106.13156/) (2021)
- [PRedItOR: Text Guided Image Editing with Diffusion Prior](https://mlsanity.com/paper/2302.07979/) (2023)
- [Generative Flows with Invertible Attentions](https://mlsanity.com/paper/2106.03959/) (2021)
- [Two-stage Visual Cues Enhancement Network for Referring Image Segmentation](https://mlsanity.com/paper/2110.04435/) (2021)
- [CHATEDIT: Towards Multi-turn Interactive Facial Image Editing via Dialogue](https://mlsanity.com/paper/2303.11108/) (2023)
- [Region-aware Knowledge Distillation for Efficient Image-to-Image Translation](https://mlsanity.com/paper/2205.12451/) (2022)
- [FastEdit: Fast Text-Guided Single-Image Editing via Semantic-Aware Diffusion Fine-Tuning](https://mlsanity.com/paper/2408.03355/) (2024)
- [FRIH: Fine-grained Region-aware Image Harmonization](https://mlsanity.com/paper/2205.06448/) (2022)
- [InvGAN: Invertible GANs](https://mlsanity.com/paper/2112.04598/) (2021)
- [GANzilla: User-Driven Direction Discovery in Generative Adversarial Networks](https://mlsanity.com/paper/2207.08320/) (2022)
- [Global-Local Image Perceptual Score (GLIPS): Evaluating Photorealistic Quality of AI-Generated Images](https://mlsanity.com/paper/2405.09426/) (2024)
- [DocEdit-v2: Document Structure Editing Via Multimodal LLM Grounding](https://mlsanity.com/paper/2410.16472/) (2024)
- [Language-based Photo Color Adjustment for Graphic Designs](https://mlsanity.com/paper/2308.03059/) (2023)
- [GANravel: User-Driven Direction Disentanglement in Generative Adversarial Networks](https://mlsanity.com/paper/2302.00079/) (2023)
- [Instilling Multi-round Thinking to Text-guided Image Generation](https://mlsanity.com/paper/2401.08472/) (2024)
- [A Survey of Multimodal Composite Editing and Retrieval](https://mlsanity.com/paper/2409.05405/) (2024)
- [I Want This Product but Different : Multimodal Retrieval with Synthetic Query Expansion](https://mlsanity.com/paper/2102.08871/) (2021)
- [CAISE: Conversational Agent for Image Search and Editing](https://mlsanity.com/paper/2202.11847/) (2022)
- [ASSET: Autoregressive Semantic Scene Editing with Transformers at High Resolutions](https://mlsanity.com/paper/2205.12231/) (2022)
- [Guiding Users to Where to Give Color Hints for Efficient Interactive Sketch Colorization via Unsupervised Region Prioritization](https://mlsanity.com/paper/2210.14270/) (2022)
- [GANalyzer: Analysis and Manipulation of GANs Latent Space for Controllable Face Synthesis](https://mlsanity.com/paper/2302.00908/) (2023)
- [Controlling the Output of a Generative Model by Latent Feature Vector Shifting](https://mlsanity.com/paper/2311.08850/) (2023)
- [Editable Stain Transformation Of Histological Images Using Unpaired GANs](https://mlsanity.com/paper/2312.03647/) (2023)
- [Experts-Guided Unbalanced Optimal Transport for ISP Learning from Unpaired and/or Paired Data](https://mlsanity.com/paper/2512.05635/) (2025)
- [Leveraging LLMs for On-the-Fly Instruction Guided Image Editing](https://mlsanity.com/paper/2403.08004/) (2024)

## Abstract (arXiv)

Most existing text-to-image synthesis tasks are static single-turn generation, based on pre-defined textual descriptions of images. To explore more practical and interactive real-life applications, we introduce a new task - Interactive Image Editing, where users can guide an agent to edit images via multi-turn textual commands on-the-fly. In each session, the agent takes a natural language description from the user as the input and modifies the image generated in the previous turn to a new design, following the user description. The main challenges in this sequential and interactive image generation task are two-fold: 1) contextual consistency between a generated image and the provided textual description; 2) step-by-step region-level modification to maintain visual consistency across the generated image sequence in each session. To address these challenges, we propose a novel Sequential Attention Generative Adversarial Net-work (SeqAttnGAN), which applies a neural state tracker to encode the previous image and the textual description in each turn of the sequence, and uses a GAN framework to generate a modified version of the image that is consistent with the preceding images and coherent with the description. To achieve better region-specific refinement, we also introduce a sequential attention mechanism into the model. To benchmark on the new task, we introduce two new datasets, Zap-Seq and DeepFashion-Seq, which contain multi-turn sessions with image-description sequences in the fashion domain. Experiments on both datasets show that the proposed SeqAttnGANmodel outperforms state-of-the-art approaches on the interactive image editing task across all evaluation metrics including visual quality, image sequence coherence, and text-image consistency.