Image Editing
8 papers with code • 1 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Image Editing
| Trend | Dataset | Best Model | Paper | Code | Compare |
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ImgEdit-Data
Subtasks
Most implemented papers
InstructPix2Pix: Learning to Follow Image Editing Instructions
timothybrooks/instruct-pix2pix
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CVPR 2023
We propose a method for editing images from human instructions: given an input image and a written instruction that tells the model what to do, our model follows these instructions to edit the image.
In-Context Editing: Learning Knowledge from Self-Induced Distributions
bigai-ai/ICE
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In scenarios where language models must incorporate new information efficiently without extensive retraining, traditional fine-tuning methods are prone to overfitting, degraded generalization, and unnatural language generation.
Emerging Properties in Unified Multimodal Pretraining
Unifying multimodal understanding and generation has shown impressive capabilities in cutting-edge proprietary systems.
ImgEdit: A Unified Image Editing Dataset and Benchmark
To ensure the data quality, we employ a multi-stage pipeline that integrates a cutting-edge vision-language model, a detection model, a segmentation model, alongside task-specific in-painting procedures and strict post-processing.
UniWorld-V1: High-Resolution Semantic Encoders for Unified Visual Understanding and Generation
Although existing unified models achieve strong performance in vision-language understanding and text-to-image generation, they remain limited in addressing image perception and manipulation -- capabilities increasingly demanded in practical applications.
MagicBrush: A Manually Annotated Dataset for Instruction-Guided Image Editing
osu-nlp-group/magicbrush
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NeurIPS 2023
To address this issue, we introduce MagicBrush (https://osu-nlp-group. github. io/MagicBrush/), the first large-scale, manually annotated dataset for instruction-guided real image editing that covers diverse scenarios: single-turn, multi-turn, mask-provided, and mask-free editing.
UltraEdit: Instruction-based Fine-Grained Image Editing at Scale
This paper presents UltraEdit, a large-scale (approximately 4 million editing samples), automatically generated dataset for instruction-based image editing.
Step1X-Edit: A Practical Framework for General Image Editing
In recent years, image editing models have witnessed remarkable and rapid development.
