Recent advancements in image editing applications such as relighting, compositing, harmonization, and virtual object insertion have opened up new horizons in visual media, augmented reality, and virtual production---especially with the rise of powerful image generative models. However, evaluating the quality of results for these applications is still a significant challenge. Traditional image quality metrics are not always effective in capturing the perceptual realism and subtle effects these technologies aim to achieve. Additionally, relying on user studies can be time-consuming and introduces variability, making comparing methods consistently challenging. To address these issues, this workshop explores and develops standardized evaluation metrics to bridge the gap between quantitative assessment and qualitative perception.