Revolutionizing Sports Advertisements with Generative AI.
In the world of sports, football is a global phenomenon that captivates millions of fans worldwide. One crucial aspect of the game is the advertising hoardings that encircle the pitch, providing a unique opportunity for brands to connect with fans. With the emergence of Generative AI, football pitch advertisement boards are set to undergo a transformative change, enabling hyperpersonalized user engagement that resonates with fans like never before.
At Sngular we’ve already developed Generative tools to enhance user-brand relationships, for example, our AI team developed a tool to generate custom Rock Avatars at Tech Conferences!
You can check other Computer Vision Projects made by our team:
Now I tell you how a full pipeline for custom advertisement in football could be achieved! This article is a guide trought a simple proof of concept (took me less than two days) and is far from an MVP.
The Power of Generative AI in Advertising
Generative AI, a technology built on sophisticated neural networks, has the ability to create content that is remarkably similar to what a human can produce. In the realm of advertising, this means that AI can now generate hyperpersonalized user ads that cater to the unique preferences, habits, and needs of individual consumers. This transformation is not limited to traditional display ads but extends to video, social media, and even audio content.
Creating Highly Targeted Ads
The cornerstone of hyperpersonalized advertising is the in-depth understanding of user behavior. AI leverages vast datasets and cutting-edge algorithms to analyze user interactions, click-through rates, purchase history, social media activity, and much more. By processing this information, AI models can create user profiles that go far beyond basic demographics. They can now predict the products, services, or content that a user is most likely to engage with.
With this wealth of data at its disposal, Generative AI can craft advertising content that speaks directly to an individual. For instance, a user who frequently searches for hiking trails may see ads featuring the latest outdoor gear and adventure destinations. Conversely, someone with a penchant for cooking might encounter ads promoting gourmet kitchen gadgets or culinary classes.
Adapting to Real-Time Changes
Hyperpersonalized user ads are not static; they can adapt to changing user preferences. If an individual’s behavior shifts, the AI can quickly modify the advertising content to match their new interests. This level of agility ensures that advertising is always relevant and engaging, which is crucial in the highly competitive digital advertising space.
The Pipeline for custom Advertisements
The whole pipeline can be divided in 3 steps:
1. Image Segmentation with SAM Model: Begin by using the SAM Model to accurately segment the football pitch image, isolating the advertising hoardings.
2. Convert Segments to Embeddings with CLIP: Transform the segmented masks into embeddings using CLIP, enabling custom prompt-masking. For example, in this case we could ask the Pipeline to change only the content of pitch advertisement boards.
3. Stable Diffusion Inpainting for Hyperpersonalization Ads: Apply Stable Diffusion inpainting to replace the existing content on the hoardings with personalized brand advertisements, creating a dynamic, personalized viewing experience for fans.
Step 1: Segment the Image with SAM Model
The journey begins with the use of the state-of-the-art SAM Model, developed by META AI. SAM excels at segmenting images with unparalleled accuracy, providing us with a clear and precise canvas of the football pitch. This initial segmentation step is crucial as it isolates the pitch and its advertising hoardings, setting the stage for the subsequent personalized ad transformation.
Step 2: Convert Masks to Embeddings with CLIP
Following the image segmentation, we leverage CLIP, a cutting-edge AI model. CLIP’s capabilities extend to converting image segments, or masks, into embeddings — numerical representations of visual content. Then we could select specific objects in the image using natural languaje, particularly the football pitch advertisement hoards. Now that we have selected the region in the image that we want to personalize, we can start creating our custom advertisements.
Step 3: Use Stable Diffusion Inpainting to Generate Ads
Now we can leverage the whole potential of inpainting text-to-image models like Stable Difussion. The result is hyperpersonalized advertisements that resonate with fans on a highly individualized level. This step replaces the existing content on the advertisement hoardings with brand advertisements, seamlessly integrating the personalized content into the live match environment.
This advanced AI pipeline ensures that football pitch advertisements evolve into dynamic canvases that deeply engage fans with brands, products, and experiences that align with their unique interests and preferences.
As you can see results are far from being optimal but keep in mind that there is a lot of room for improvent as I only tried one model with no tweaking on pre or posprocessing or prompting. The concept is there, and will be a standard in a near future.
The Future of Advertising
As Generative AI continues to evolve, we can expect further advancements in hyperpersonalization. This technology is not limited to e-commerce or product advertising; it can be harnessed across various sectors, including news media, entertainment, and educational content. Users can receive news tailored to their interests, streaming recommendations based on their viewing history, or educational material designed to meet their specific learning needs.
In conclusion, the era of personalized user ads in media, driven by Generative AI, is a game-changer for the advertising industry. It provides an opportunity for brands to engage with users on a level that was previously unimaginable, all while respecting user privacy. As this technology continues to mature, we can look forward to a more relevant, engaging, and personalized advertising experience for consumers, ultimately benefiting both advertisers and their audiences.
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