The Power of GenAI for OTT Industry

Generative AI is changing how media content is created and delivered in the streaming industry. Companies are using advanced tools to enhance video quality, edit content, and make interactions smarter and more dynamic. Media services now focus on secure uploads, fast cloud processing, and stable worldwide delivery.

Table of Contents

Although these advances bring many benefits, challenges remain in areas like video compression, subtitle generation, and adapting content for different devices. AI-powered solutions help solve problems such as restoring lost video quality, making subtitles easier, and supporting multiple video formats efficiently.

Key Takeaways

Generative AI improves media content creation and delivery.
Video processing faces challenges like compression and device adaptation.
AI models offer effective solutions for the media industry’s needs.

Generative AI Use Cases in Streaming Media Platforms

1. Improving Visual Quality for Online Video

Generative AI tools help restore video quality that is lost during compression. These models can make blurry or blocky videos look clearer, reduce noise, and bring out details in faces or backgrounds. The AI can also customize how strong the enhancement is, meeting different viewer preferences.

Streaming services depend on smaller file sizes to reduce costs, but that often means lower quality. By using AI-powered codecs and processing, video files can be compressed by up to 70% while keeping the quality high. Some systems are also built to handle 3D and multi-view content, saving more data when streaming to devices like headsets.

AI Feature	Benefit
Noise Reduction	Cleaner, clearer playback
Detail Enhancing	Sharper visuals
Smart Compression	Smaller files, same quality
Real-time Performance	Fast enough for live video

2. Smarter Video Analysis and Automated Editing

Generative AI models are used to better understand and edit video content. They can automatically generate subtitles in multiple languages, making content accessible for global audiences. If a video already has hardcoded subtitles, AI can detect and erase them, allowing new subtitles in a different language to be added.

AI can also highlight key moments in a video, such as important events in sports. This saves time by quickly finding and editing clips that viewers want to see.

Tasks made easier with AI:

Subtitle generation and translation
Content tagging for quick search
Removing and replacing on-screen text
Creating highlight reels

3. Creating AI-Powered Interactive Features

Generative AI is used to build interactive features that make the viewing experience more engaging. It enables real-time interaction between viewers and AI systems during live streams or on-demand videos.

Examples include:

Adaptive streaming quality based on network conditions
Server-side ad insertion for targeted content
Time-shifted viewing so viewers can pause and catch up on live events

These AI-powered features help make streaming smoother, more personal, and accessible to more people.

Summary of Tencent Cloud Video Solutions

1. Safe and Fast Video Upload

Tencent Cloud supports an easy and secure way to upload video files. This upload process is designed for speed and safety, making sure that videos get to the cloud quickly without risking data loss or theft. Files are protected during transfer so users can trust their content will arrive intact.

2. Smart Media Enhancement and Editing

The platform handles media processing with advanced AI models. It offers tasks like video transcoding, automatic subtitles, and blurring of sensitive content. AI can also improve video quality, reduce noise, sharpen details, and make faces clearer. It supports the replacement of subtitles and highlights important video moments, like key plays in a sports game.

Supported media processing features include:

Compression and Transcoding: Reduces file size while keeping high visual quality.
Automatic Subtitles: Generates subtitles in different languages, cutting down human workload.
Sensitive Information Editing: Detects and blurs private or sensitive parts of videos.
Recreation & Highlight Extraction: AI creates highlights by focusing on key segments, such as sports goals.

Feature	Description
Video Quality Enhancement	Improves sharpness, brightness, and clarity
Noise Reduction	Removes blur blocks and unwanted video noise
Subtitle Handling	Adds, switches, or removes subtitles

3. Flexible Video Playback and Streaming

Tencent Cloud provides streaming that adjusts to different network conditions and device settings. Users can watch live or on-demand videos, and the system supports time shifting and ad insertion. The streaming technology adapts to changes in internet speed and device orientation, so videos look good on both phones and big screens.

Key benefits:

Adaptive Playback: Delivers the best quality for each viewer.
Support for Multiple Codecs: Compatible with common video formats.
3D and Multi-view Video: Efficient handling for new devices like VR headsets with up to 50% lower bandwidth requirements.

4. Reliable and Wide-reaching Content Distribution

Content is delivered by a global, stable network. This makes sure that videos load quickly and play smoothly anywhere in the world. Tencent Cloud’s delivery network is built to keep video streaming reliable, even if viewers are far from the original source. All users get a fast and high-quality viewing experience.

To optimize delivery even further, streaming platforms can benefit from using a tool to calculate bandwidth, helping them plan infrastructure more accurately and ensure consistent performance across all regions.

Delivery network features:

High-speed global connections
Consistent video quality for users in different regions
Reduced delays and buffering

Main Problems in Media Handling

1. Image and Sound Quality Decreases When Compressing Files

Many videos are made smaller to save storage space and to make online streaming faster. However, shrinking files almost always reduces their sharpness and quality. Viewers may notice blurry spots or blocks in the picture, as well as extra noise, especially after strong compression. Balancing file size and quality is difficult, since higher quality usually means bigger files.

Key Points:

Compression makes videos smaller but can blur details
Filming and viewing devices support different formats
New codecs aim to reduce file size while maintaining quality

Challenge	Impact
Lowered quality	Less clear videos
Format compatibility	Playback issues
Compression artifacts	Visual distortion

2. Creating Subtitles in Many Languages

Adding subtitles helps people around the world understand videos. Manually creating these subtitles is a slow, tiring job that requires familiarity with many languages. Accurate, automatic subtitle generation is needed, but making it work well for lots of languages is not easy.

Steps in Subtitling:

Detect spoken words correctly
Translate into many languages
Overlay subtitles clearly on video

3. Fitting Videos to Different Screen Shapes

Phones, tablets, and TVs can all have different shapes and sizes. Changing a video to fit every screen, whether it’s tall or wide, takes special editing. If videos are not adapted, viewers may see black bars or parts of the video may get cut off.

Problems:

Different devices use different aspect ratios
Need to keep important content visible
Automatic resizing is required for smooth viewing

4. Automatic Creation and Editing of Content

Viewers often want only the most important or exciting parts of a long video, like the best moments in a sports game. Changing or recreating content automatically requires smart technology. For example, removing subtitles that are already part of the video and adding new ones in another language involves several steps and advanced tools.

Uses:

Highlighting key events
Replacing or updating existing onscreen text
Customizing content for special needs or languages

AI-Powered Tools for Media Workflows

1. Improving Video Quality with Advanced Models

Many videos lose quality after being compressed to save storage and reduce bandwidth costs. This often leads to visible artifacts, noise, and unclear details. AI models have been developed to restore video quality, making faces and key areas sharper while reducing unwanted noise.

Some of these techniques include:

Noise Reduction: Removes unwanted grain or static from video.
Detail Enhancement: Boosts the clarity of key subjects, such as presenters.
Flexible Enhancement Levels: Users can adjust how much improvement they want for different preferences.

Feature	Benefit
Noise Removal	Cleaner, clearer videos
Detail Boost	Sharper faces and subjects
Customizable Strength	Matches different viewing needs

Model structure is designed to run efficiently, supporting real-time processing without slowing down playback.

2. Automated Subtitle Handling and Language Adaptation

Creating and managing subtitles by hand is time-consuming. AI-driven subtitle detection can identify existing subtitles in a video. When a subtitle is already encoded into a video, these tools help detect and remove it.

AI models can then add new subtitles in the desired language, making video content accessible to viewers around the world. This process reduces manual work and overcomes language barriers.

Process Steps:

Detecting existing subtitles.
Remove or mask them using generative AI.
Add new subtitles in selected languages.

This helps reach wider audiences while saving time and effort.

3. Extracting Key Moments from Content

Finding important segments in videos, like highlights from a sports match, is another challenge. AI models can quickly identify and extract these key events—such as a goal in a football game—so viewers can watch only the most relevant parts.

Examples of extracted highlights include:

Major sports moments (e.g., goals, scoring plays)
Key scenes in news or entertainment videos

This tool is especially useful for making quick recaps or summaries, allowing users to engage with only the most important content.

How to Improve Video Encoding and Compression Methods

1. Streamlined Codec Choices for Network Savings

Choosing the right codec is important for reducing the size of video files. Smaller files help save on storage space and cut down network costs. By using optimized encoding, compression rates can reach up to 70%, shrinking files without making the video look worse to viewers.

A comparison showed that this approach lowered the bit rate by 32% when tested against common open-source codecs. The video quality stayed almost the same, even with a much smaller file.

2. Broad Support for Major Video Types

To make sure everyone can watch videos, support for a wide range of popular video formats is needed. The system is designed to work with the most common video codecs. This means that the content can be played back smoothly on different devices and software platforms.

Some key supported formats include:

Format Type	Device/Platform Compatibility
H.264/AVC	Most browsers, computers, mobiles
HEVC/H.265	New smartphones, smart TVs, computers
Multi-view HEVC (3D)	Devices like the Apple Vision Pro

3. Superior Compression Results

Video compression methods focus on shrinking files as much as possible while keeping the look of the video clear. Current solutions can often achieve around 30% more compression than standard approaches, with the final file size sometimes dropping to a quarter of the original.

For advanced 3D videos, using multi-view HEVC allows for both left and right views to share data. This leads to up to 50% less data usage, while only needing about 10% more time for processing. This allows for efficient streaming and storage of 3D and VR content.

Advances in Modern Video Formats

3D and Multiple View Video Capabilities

New video formats now support 3D and multi-view features. In older methods, a separate video stream was made for each eye when creating 3D videos. This doubled storage needs and made it harder to manage files.

With newer multi-view technology, systems can combine similar parts of each video stream. This can reduce the total bitrate by about 50% compared to the traditional method. According to testing, this modern process only takes about 10% more time than the old way, but it saves a lot of space and bandwidth.

Here’s a simple comparison:

Method	Bitrate Required	Processing Time
Traditional Dual Streams	High	Normal
Multi-View (Latest)	About 50% lower	About 10% higher

These improvements make it easier and more affordable to deliver 3D and multi-view content.

Connecting with Apple Vision Pro

Recent updates have included support for Apple Vision Pro, a headset that uses advanced video technologies. The new multi-view encoding works well with this device. This allows users to watch 3D videos with better quality and lower data use.

The video technology adapts to Apple Vision Pro by using efficient encoding formats. These formats take advantage of shared areas between streams for each eye. As a result, video looks sharp while saving bandwidth and storage, making it smooth for viewers using Apple Vision Pro.

Efficient for new devices
Reduces file sizes
Keeps high quality for better experiences

Smart Video Restoration Methods

1. On-the-Fly Model Improvement

For video quality restoration, it is important that models work quickly. They need to deliver results with low delays, especially for live streaming or real-time applications.

To achieve this, the design aims for smaller, more efficient models. For example, using a student-teacher approach lets a larger “teacher” model help train a smaller “student” model. The smaller model then runs much faster. Only high-precision calculations are used during the final steps, which also cuts down the time.

Key methods for real-time improvement:

Use compact model structures
Optimize for CPU usage
Employ precise calculations only when necessary

2. Custom Enhancement Settings

Not every viewer wants a video to look the same. Some people prefer brighter images, while others may want less sharpness or more natural detail.

The system supports adjusting enhancement levels. Users or service providers can set how strong the video improvement should be. This makes the experience more personal and lets the video match different viewing preferences.

Example preferences:

User Type	Preferred Setting
Sports viewers	High sharpness
Drama fans	Softer, warmer colors
News watchers	Clear faces, less noise

3. Speeding Up AI Models

To make video restoration practical, the models should not slow down streaming or playback. Several techniques help the system process videos faster.

Selected acceleration strategies:

Use distillation to shrink model sizes
Split large tasks into smaller, targeted jobs (e.g., denoising, face enhancement)
Optimize inference time by focusing only on the most important areas in each frame

These steps help maintain video quality without causing buffering or lag.

4. AI Tools for Specific Restoration Tasks

Different problems in video require different tools. A “one size fits all” model does not always work as well.

Specialized AI models address particular tasks, such as:

Reducing compression noise
Bringing out more detail in faces
Enhancing important objects while keeping backgrounds natural

This focused approach allows each part of the video to get the best enhancement possible, leading to higher-quality playback for users.

Key Takeaways

The team at Tencent Cloud focuses on improving video quality and content management through advanced AI models. Their work addresses common problems like data loss from compression, language barriers, and varied device aspect ratios. AI tools allow quick and secure video upload to the cloud and automate tasks like transcoding and adding subtitles.

They use generative AI models to restore video quality and change subtitles without manual editing. Their technology helps deliver clear, high-quality video efficiently, even when files are heavily compressed. The codec they’ve developed supports many formats and achieves up to 70% compression, saving bandwidth without major quality loss.

Adaptive processing adjusts videos for different devices, ensuring consistent viewing experiences. The system also helps highlight key moments in videos, such as important sports scenes, with minimal effort. Through careful model design and optimization, the team reduces processing times and supports real-time enhancement.