mlsanityData to 7 Oct 2026

Hyper-parameter tuning for text guided image editing

arXiv 2407.21703 ↗First posted 31 Jul 2024cs.CVcited by 2

Not on the map. Why?

Abstract (arXiv)

The test-time finetuning text-guided image editing method, Forgedit, is capable of tackling general and complex image editing problems given only the input image itself and the target text prompt. During finetuning stage, using the same set of finetuning hyper-paramters every time for every given image, Forgedit remembers and understands the input image in 30 seconds. During editing stage, the workflow of Forgedit might seem complicated. However, in fact, the editing process of Forgedit is not more complex than previous SOTA Imagic, yet completely solves the overfitting problem of Imagic. In this paper, we will elaborate the workflow of Forgedit editing stage with examples. We will show how to tune the hyper-parameters in an efficient way to obtain ideal editing results.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 14 of its 15 references that are in the map. First posted on arXiv 31 Jul 2024.

Builds on

14 of 15 references.

References · 14

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  3. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,322
  4. 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,466
  5. 2022BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generationcited by 4,310
  6. 2022VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Trainingcited by 1,305
  7. 2022Imagic: Text-Based Real Image Editing with Diffusion Modelscited by 1,172
  8. 2016Temporal Segment Networks: Towards Good Practices for Deep Action Recognitioncited by 899
  9. 2024Diffusion Model-Based Image Editing: A Surveycited by 212
  10. 2020TDN: Temporal Difference Networks for Efficient Action Recognitioncited by 183
  11. 2020V4D:4D Convolutional Neural Networks for Video-level Representation Learningcited by 33
  12. 2023Forgedit: Text Guided Image Editing via Learning and Forgettingcited by 26
2 more
  1. 2022TFCNet: Temporal Fully Connected Networks for Static Unbiased Temporal Reasoningcited by 12
  2. 2020Knowledge Integration Networks for Action Recognitioncited by 7

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 1; 2026: 1.

2 papers.

  1. 2025CDST: Color Disentangled Style Transfer for Universal Style Reference Customizationcited by 6
  2. 2026Style-CCL: Content-Preserving Style Transfer via Curriculum Continual Learningcited by 1