Adobe GigaGAN Upscaler | Say Goodbye to Blurry Videos Forever!

What is GigaGAN

VideoGigaGAN is an innovative AI application developed by Adobe. It is a new generative model for VSR (Video Super Resolution) to produce videos with high-frequency details. It elevates low-resolution and blurry videos to impressive high-resolution quality while maintaining temporal consistency in preserving the crucial details. The backbone of this breakthrough is a robust and large-scale image upsampler, GigaGAN. 

Based on the previously demonstrated app, GigaGAN, that improved old photos or generated new ones, VideoGigaGAN is the improved version. Using the darn impressive VideoGigaGAN, you get stunning HD quality up to eight times its original resolution (128×128→1024×1024). Unlike previous methods like VSR, VideoGigaGAN tackles the upscaling challenge without introducing any flickering issues. It goes beyond mere enhancement, adding intricate details and sharpness that were previously unattainable. 

Features of GigaGAN Upscaler

GigaGAN super resolution is the result of Adobe researchers that can accept a blurry video sample and return the same with greatly enhanced sharpness and clarity. GigaGAN 4K is an AI that can help create realistic images. It specializes in upscaling real photos and generated content and is a viable option for text-to-image synthesis. You may also interested in how to unblur videos. Here's more to its claims: 

1. GigaGAN incorporates a disentangled, continuous, and controllable latent space. This means that different aspects of the input data, such as style and content, are separated and can be manipulated independently within this space.

2. For layout-preserving fine style control, GigaGAN utilizes a technique where it applies distinct prompts, or instructions, at fine scales within the image. This allows for precise adjustments to specific details or elements in the image while maintaining the overall layout and structure.

3. GigaGAN allows users to alter the texture of an image while fixing the layout through the use of prompts. In this context, prompts serve as instructions or guidance for the model to follow during the image generation process. By providing prompts that focus on fixing or maintaining the layout of the image, users can ensure that the overall structure and composition remain unchanged.

4. GigaGAN alters image style while maintaining layout integrity through targeted prompting. This means users can guide style changes without compromising the original image layout.

5. The GigaGAN framework helps train an efficient and higher-quality upsampler for real images. It also comes in handy when applied to different text-to-image output models, such as diffusion. 

6. GigaGAN is equipped to synthesize ultra-high resolution images at 4K resolution in less than 4 seconds (3.66 seconds to be exact.)

7. GigaGAN allows smooth interpolation between prompts while retaining a disentangled latent space to help users combine the coarse style of one sample with the fine style of a different sample. It can directly control the style with text prompts. 

Pros of VideoGigaGAN

The versatility of VideoGigaGAN goes far beyond simple upscaling, opening up a wide range of applications such as enhancing archival footage, improving low-quality videos, and even enabling real-time video processing. Although still under development, the idea of integrating VideoGigaGAN into Adobe's suite of creative tools presents an exciting prospect. GigaGAN primarily offers three significant advantages: 

1. GigaGAN's order of magnitude is quicker at inference time, allowing users to synthesize a 512-pixel image in less than 0.13 seconds.  

2. GigaGAN helps synthesize high-resolution images in less time, such as a 16-megapixel image that takes no longer than 3.66 seconds.

3. Integration of various advanced techniques helps improve temporal consistency and detail preservation. 

4. VideoGigaGAN aims to balance temporal stability and fine details to enhance the videos for optimal results. 

5. VideoGigaGAN facilitates a range of latent space editing applications, such as:

• Vector arithmetic operations: to add, subtract, or scale vectors to achieve specific changes in style or content.

• Latent Interpolation: for a smooth transition between two latent representations to generate intermediate images with gradual changes in style or content.

• Style mixing: to blend or combine different styles by manipulating the latent space representations of multiple images, resulting in new, hybrid styles.

Limitations of VideoGigaGAN

While VideoGigaGAN's video quality seems really good, its limitations are quite restrictive. These drawbacks certainly have the scope for improvement to serve the users in a better way. 

1. Processing highly long videos, such as over 200 frames or more, is challenging due to misguided feature propagation caused by inaccurate optical flow in the extended video sequences. 

2. Struggle to perform effectively on small objects like texts and characters because the information concerning them is significantly lost in the LR video input.

3. Notably, larger model size. 

4. High dependence on the accuracy of the estimated optical flow.

How to Use VideoGigaGAN

The Video Super-Resolution (VSR) model extends the asymmetric U-Net architecture of the image-based GigaGAN upsampler for handling video data. The new models offer a detail-rich result with comparable temporal consistency compared to the previous models. 

1. The model includes various crucial elements to put in temporal consistency over time across video frames. Temporal attention layers are integrated within the decoder blocks to inflate the image upsampler into a video upsampler. This way, the GigaGAN model can effectively capture and propagate temporal information. 

2. To enhance temporal consistency, a flow-guided propagation AI module is added right before the main GAN. It will understand the objects' movement over time in the initial video so that the upscaled video has the same smooth movement. The inflated GiGAGAN will get temporally aware features through optical flow estimation with this module. A recurrent neural network will also be employed to align and propagate features across all the video frames. 

3. Anti-aliasing blocks have replaced the standard downsampling layers to tackle aliasing and mitigate the artifacts caused by the encoder's downsampling operations. These blocks utilize a technique where they first apply a filter that removes high-frequency components from the video, then reduce the resolution through subsampling. This process reduces unwanted visual artifacts like aliasing and flickering that may occur over time in the output video.

4. A high-frequency feature shuttle is implemented to counterbalance the loss of high-frequency details resulting from the anti-aliasing process. This mechanism uses skip connections to transfer high-frequency features directly from the encoder to the decoder. 

Unlike the standard process where features pass through the BlurPool operation in the anti-aliasing blocks, these skip connections bypass the BlurPool step entirely. Doing so ensures that crucial high-frequency details are preserved and transmitted intact from the encoder to the decoder, mitigating the blurring effect of the anti-aliasing process. It helps maintain sharpness and clarity in the final output while benefiting from improved temporal consistency.

Best GigaGAN Upscaler Alternative - UniFab Video Upscaler AI 

However, beginners and novices can struggle with its working if they are unfamiliar with Adobe's UI and other necessary tools. Also, as of now, the system's announcement is a mere demonstration and not a pending release, so it is dubious whether Adobe will release it for general use. In such a case, you can use professional yet friendly software like UniFab Video Upscaler AI. 

This AI Video Upscaler is a reliable solution for expats and beginners to upscale low-resolution videos utilizing AI technology. It helps enhance the overall clarity and quality of video regardless of its type. Its trained AI models can recognize, analyze, and enhance your video with deep learning algorithms for a more accurate and lifelike visual effect. Enlarge your video resolution to 720p and 1080p Full HD or up to an impressive 4K/8K Ultra HD for every genre within a few minutes. 

Key Attractions of UniFab Video Upscaler AI 

• Up to 8K Resolution

Enlarge video resolutions up to 8K using advanced AI for sharper and clearer images.

• Deep Learning Algorithms

AI modes are trained to recognize, analyze, and enhance video content, delivering vivid, realistic visuals.

• Universal & Animation Model

Upscale videos to 720p, 1080p, 4K, or 8K, with excellent results for black-and-white movies, low-resolution TV shows, home footage, and animations.

• 50x Faster with GPU Acceleration

Leverages NVIDIA CUDA, AMD, and Intel Quick Sync for up to 50x faster video enhancement or conversion.

• User-Friendly Interface

Simple, intuitive interface, perfect for beginners.

• Built-in Editing Tools

Allows users to crop, trim video clips, adjust audio, and more for added customization.

• Customizable Output Settings

Adjust video quality, resolution, frame rate, bitrate, codec, and other parameters for tailored output.

• Two Free AI Tools Supported

Download UniFab and enjoy free access to Vocal Remover AI and Video Background Remover AI. Plus, other features are available for a 30-day free trial with no watermark.

How to Upscale Videos With UniFab

Conclusion

Adobe's VideoGigaGAN signifies a significant leap forward in AI-driven video upscaling. It merges the capabilities of Generative Adversarial Networks (GANs) with a meticulous focus on detail. This innovation promises to revolutionize video enhancement, allowing users to transform mundane footage into visually captivating masterpieces. 

As this technology evolves, it's expected to integrate seamlessly into mainstream software applications to empower users across various industries and skill levels and elevate the quality of their videos effortlessly. Whether enhancing home videos, refining professional footage, or creating stunning visual effects, VideoGigaGAN opens up a world of endless possibilities for content creators and enthusiasts alike.

FAQs about GigaGAN

Can I get 8x super resolution with VideoGigaGAN?

Yes. Compared to the state-of-the-art VSR methods, VideoGigaGAN offers superior results. It produces videos with remarkable time consistency and even improves the appearance details at 8x super resolution. If you're interested in exploring more tools for enhancing video quality to 8K, check out our article on 8K Video Enhancer, where we dive into various tools and their processing effects.

Is GigaGAN open source?

No, GigaGAN is not open source. It is a proprietary technology, and the full version is not available for public use or modification. If you're looking for open source video upscaler, there are several other options available in this article.

How can I use GigaGAN to upscale videos? 

Adobe researchers presented VideoGigaGAN in the R&D phase. So, it has yet to be introduced as a private beta version. While it helps retain sharp details, ensure smooth transitions, and upsample videos up to 8 times, it is only a research preview. Adobe has yet to make it available to consumers, and no official announcement has been made yet.

Can I upscale my low-resolution videos? 

Yes. You can use UniFab Video Upscaler to enhance and upscale your poor-quality videos with AI technology. The program can automatically recognize, analyze, and produce high-quality results, up to 8K Ultra HD effortlessly.