Interactive Image Manipulation with Natural Language Instruction Commands
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Abstract (arXiv)
We propose an interactive image-manipulation system with natural language instruction, which can generate a target image from a source image and an instruction that describes the difference between the source and the target image. The system makes it possible to modify a generated image interactively and make natural language conditioned image generation more controllable. We construct a neural network that handles image vectors in latent space to transform the source vector to the target vector by using the vector of instruction. The experimental results indicate that the proposed framework successfully generates the target image by using a source image and an instruction on manipulation in our dataset.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 23 Feb 2018.
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Citing papers per year: 2021: 1; 2022: 2; 2023: 0; 2024: 1.
4 papers.
- 2022EnvEdit: Environment Editing for Vision-and-Language Navigationcited by 83
- 2021M3L: Language-based Video Editing via Multi-Modal Multi-Level Transformerscited by 8
- 2024A Survey of Multimodal Composite Editing and Retrievalcited by 5
- 2022CAISE: Conversational Agent for Image Search and Editingcited by 3
- 2024A Survey of Multimodal Composite Editing and Retrieval9 Sep 2024
- 2022EnvEdit: Environment Editing for Vision-and-Language Navigation29 Mar 2022
- 2022CAISE: Conversational Agent for Image Search and Editing24 Feb 2022
- 2021M3L: Language-based Video Editing via Multi-Modal Multi-Level Transformers2 Apr 2021