How to Remove Background & Replace(Generate) a New One?

Image background processing is considered to be the crown of image processing technology. This is because many challenges need to be solved, including identifying the boundary between the object and the background, determining the shape and location of the object, and generating a suitable new background.
This requires the use of various methods of computer vision and image processing, such as image segmentation, object detection and recognition. This in turn can be achieved by a variety of deep learning networks such as convolutional neural networks (CNNs), generative adversarial networks (GANs) and ConvLSTM, which require large amounts of high-quality data for training.
In practical applications, using AI to process image backgrounds requires a high level of engineering and research capabilities. Currently, there are some relatively successful applications in the technology and commercial sectors, but there are still many opportunities and challenges for researchers to address.

  • Why people need to remove the image background and replace it?
  1. The original background does not meet the requirements, you need to replace it with a more appropriate: For example, the photo of the ID generally needs a white or blue background
  2. The original background is too cluttered and needs to be replaced with a cleaner background.
  3. The original background interferes with the display of the object and needs to be replaced with a transparent one. For example, for the main image of an e-commerce product or POD
  4. To better display the object, it needs to be replaced with one that fits the theme. For example, product poster images
  5. The image background needs to be replaced for commercial or advertising purposes.
  6. Excellent visual effects
  7. And more for other reasons

There are several ways to remove the background from an image, commonly used methods include:
The magic wand or lasso tool in photo editing software (such as Adobe Photoshop or GIMP)
The “Remove Background” tool in Microsoft PowerPoint
Using deep learning algorithms such as Full Convolutional Networks (FCN) for semantic segmentation, which can be trained to accurately separate the subject from the background in complex images
Online background removal tools, such as, which use AI to automatically remove backgrounds
Manually use the brush or eraser tool in editing software

In addition to the above method, there is a more convenient function to remove and replace the background:

Background Diffusion

  • What is the meaning of the name “background diffusion”?

The target of processing “background” + the most powerful generation algorithm “stable diffusion” = the practical background tool “background diffusion”. In addition, “diffusion” has a hidden meaning, we’ll mention it later. Background Diffusion is currently the first feature that combines the removal of image backgrounds and AIGC, currently only runway’s “Backdrop Remix” has similar features on the web (but it is not officially released yet, only demos can be seen)

  • What is the difference between background diffusion and the traditional remove+replace background?
  1. The two steps of removing background and uploading backgroundless images are skipped: the images can be processed directly on the operation page, saving a lot of time
  2. If you want to replace the background, you have to search for it in free image resource sites, and often the result is that you can’t find a satisfactory image. Background Diffusion, on the other hand, automatically generates the background you want by typing in the prompt, and if there is a defect, you can regenerate it infinitely.
  3. The backgrounds chosen are derived from photographs or reality (monochrome, colorful, complex). Generated backgrounds are different and contain infinite inspiration. It may be a background you have never seen before, bringing you the most spectacular visual enjoyment!

Background Diffusion represents a new direction for the future, i.e. the combination of relatively traditional image processing techniques and the more innovative AIGC. Such a technological collision will undoubtedly lead to endless possibilities!