Best SVP (SmoothVideo Project) Alternative: AI Video Interpolation
Summary: What does SVP stand for? How does SVP smooth video? What is video frame interpolation? What is the best frame rate for video? Is there any good SVP alternative or video interpolation software to achieve a better viewing experience? If you are an anime or video buff taking video quality seriously, you have come to the right place! This post aims to answer such questions and offer the best alternative to SVP.
Do you know video interpolation, SVP, or other video interpolation software? If you are an anime buff or action movie lover, you must be keen on interpolation video for smooth and better viewing. Truth is that knowing the best frame rate for video leads to a perfect and immersive viewing experience. In this post, you understand what SVP stands for, know the best frame rate for video and the best SVP alternative to smooth video for the utmost cinema-like viewing result.
Table of Contents
- 1. Video Interpolation: Everything You Shall Know
- 3. Best SVP alternative: AI-driven Video Interpolation
Before getting down to SVP, it’s imperative to know the basics of the video frame, frame rate, and video (frame) interpolation.
Back in childhood, you must have been keen on cool little flipbooks where a stack of paper has an image on every page. When you flipped through the pages quickly, the image would appear to animate and move? Sounds familiar, right? This is how video works. Whether digital or old-school film, video is a series of still images that, when viewed in order at a certain speed, give the appearance of motion. Each of those images is called a “frame”. This is how video frame and frame rate come from.
To be specific, the frame rate is the speed at which those images are shown, or how fast you “flip” through the book. It’s usually expressed as “Frames per Second,” or FPS. Therefore, if a video is captured and played at 24fps, that means each second of the video shows 24 distinct still images.
With the way our brain adds missing information to create motion, the higher the FPS, the smoother the motion appears before the human eyes. In general, the minimum FPS needed that helps avoid any jerky motion is 30 frames per second. For high-motion content, you will be looking at 60 frames per second. So to speak, video frame per second, or say, video fps decides video quality and viewing experience.
Frame rate greatly affects the style and viewing experience of a video. Different frame rates result in different viewing experiences. Selecting a frame rate means taking multiple factors into accounts, such as how realistic you want your video to look, or whether or not you want to apply techniques like slo-mo (slow-motion), motion-blur effects, or transition.
Frame rates in TV and movies were standardized by The Society of Motion Picture and Television Engineers (SMPTE), but frame rates in video content haven’t been. They are used in digital cameras like DSLR, mirrorless, and smartphone devices. So, what is the best frame rate for video? There isn’t the best frame rate for video. Each frame rate example has a specific purpose, so it largely depends on what you’re shooting.
For a video on the web, most TV and film, 24 frames per second is the industry standard. Live TV including news programs, sports, and soap operas, 30 frames per second is widely accepted. Those 6 more frames per second allow for a smoother feel that works perfectly for a video that is less cinematic.
However, Hollywood-style movies are usually displayed at 24fps, since this frame rate is similar to how we see the world and creates a quite cinematic look. Live videos or videos with a lot of motion, such as sports events or video game recording, often have higher frame rates because there is a lot of action at once. In this sense, a higher frame rate will keep the motion smoother and the details crisper. Take GIFs as an example, people who create animated GIFs often sacrifice details for smaller file sizes and choose a low frame rate. Thus, GIFs are usually not that smooth and crisp as original video clips.
The most common frame rates in videos are 24, 30, and 60 fps. Now let’s dive into them one by one.
24fps: This frame rate is the one used by most Hollywood films. It makes video content seem more cinema-like. An average person may not be able to tell the difference between this frame rate and a higher one, but most professionals in film production can easily. But 24fps also has its soft rib. It will make the video look quite choppy and unprofessional if slowed down at all. If a broadcaster shoots footage to slow it down in post-production, we strongly recommend filming at a higher frame rate to make the video smooth.
Here are some situations where 24fps is widely used: HD video, landscapes if someone is speaking, and video where you want to gain details and textures.
30fps: Most modern cameras give the option to film video content in 30 frames per second. This is the best frame rate for live streaming (fps live) used for TV video content in the USA. As your camera is capturing more still images per second than it was with 24fps footage, this is ideal for sports and other fast-moving videos. If your video camera was purchased between 2000 and 2010, they will most likely only have the option to film in 30fps for live streaming fps.
To conclude, if you plan to film TV shows, vlogs, HD video, sports, and other fast-moving content, you might as well choose 30fps for smooth video viewing.
60fps: 60 frame per second video in the near equivalent to 50 frames per second one. If the camera you planning to create video content on was made in the US, it will likely enable you to film at 60 fps rather than 50. But some cameras will have the option to film in both. Such live video FPS is a high frame rate mostly used for slo-mo. In most cases, a video is recorded in 60fps will be slowed down to 24 or 30 fps for specific use. This allows for a smooth slow-motion effect during post-production.
Any frame rate that is above 60 frames per second is considered a high-speed frame rate. Some professional cameras will go as fast as 1,000 frames per second. You might have seen video examples like a bullet going in slow motion or a water balloon popping. Such fps produces special effects to make the scene more life-like. Here are the best use cases per streaming frame rate:
- The interlaced field rate of PAL.
- Some 1080p HD camera record at this frame rate
- HD video
- HD cameras record at this frame rate. Sometimes it’s referred to as 60fps, but it’s best to use 59.94 unless you really mean 60fps
- Compatible with NTSC video
- When the subject needs to present a more graceful appearance
- Adds emotions to the shot
- Slow down video shots during sporting events
- Slow down to the perfect slo-mo effect
- HD video
Based on the above examples, you must have understood the difference between 30 fps vs 60 fps video.
According to Wiki definition, Motion Interpolation or Motion-compensated Frame Interpolation (MCFI) is a form of video processing in which intermediate animation frames are generated between existing ones by means of interpolation, in an attempt to make animation more fluid, to compensate for display motion blur, and for fake slow-motion effects.
In the final analysis, the ultimate goal of Video Frame Interpolation (VFI) is to improve the frame rate and enhance the visual quality of a video by synthesizing several frames in the middle of two adjacent frames of the original video that both spatially and temporally coherent with the existing context. Video Frame Interpolation can be used to create a slow-motion video, increase video frame rate, and frame recovery in video streaming.
From web series and Internet TV to online learning and marketing, video content has dominated the digital landscape with maximum user attention. Nevertheless, a high-quality and immersive visual experience is painstakingly difficult to produce. Simply put, video frame interpolation intelligently produces missing video frames between the original ones to enhance the video’s quality and resolution so as to create a satisfactory viewing experience for the audience.
Since the emergence of video interpolation, there is some so-called traditional video interpolation software to make video smoother and better for viewing. Typical examples are SVP, DmitriRender, and PotPlayer. First, let’s quickly check the last two tools for beginners and then move to the first one designed for professionals.
DmitriRender is a DirectShow filter that can convert video frame rate in real-time and allow you to watch any movies and videos without jerks and turbidity. It calculates on the video card and inserts frames with an intermediate position of objects into the video, which can significantly improve the viewing experience. Thus, motion in the frame obtains a smooth, monolithic, fully synchronized with the output device (monitor, projector, or TV) refresh rate. This video interpolation software has some pros and cons.
- Adopts GPU-oriented algorithms for Frame Rate Conversion (FRC) and Motion-Compensated Frame Interpolation (MCFI)
- Uses modern computing capabilities, such as DXVA-decoding and GPU calculations. 64-bit mode is supported.
- Close to zero CPU load since all calculations are completed on the video card
- It requires an NVIDIA video card
- The final output can be played only on MPC
Warm tips: For most people, PotPlayer is a popular video player noted for its open-source and powerful features. But you might rarely know its hidden ability to double video frames in one click. The greatest disadvantage is that PotPlayer can merely increase video picture frames from 24fps to 48fps, unable to optimize video details.
Now it’s time to focus on SVP, the most widely-used video interpolation software able to convert any video to 60fps (and even higher) and perform this in real-time right in your favorite video player. First, let’s figure out SVP's meaning.
What is SVP? SVP stands for SmoothVideo Project that applies the same frame interpolation technique as available in high-end TVs and projectors (see “TrimensionDNM”, “Motion Plus”, “Motionflow” and others). It is designed to increase the video frame rate by generating intermediate frames between existing ones in order to produce very smooth, fluid, and clear motion. SVP 60fps is widely used for sports events and slo-mo effects.
SVP has unique features that outshine other traditional video interpolation software.
- Video frame rate conversion up to 60/120/144+ fps
- GPU acceleration, including NVIDIA Optical Flow support
- Most video players, including VLC
- HDR support (in selected players like VLC, IINA, MPV)
- VR and BD3D support (in selected players)
- Play, convert, stream
- Regular updates for Windows
- Totally free for Linux 64-bit, a 30-day free trial for Windows 10/8/7 and macOS 10.12+
However, SVP free video interpolation software is not that easy to get since it requires a license key. Besides, it takes $19.99 for a lifetime package to get regular updates (SVP4 Pro and SVP4 Mac are free for an update for lifetime users) and technical support and avoid watermarks and ads.
You can use SVP on a single Windows or macOS computer only. For additional licenses, $10 per computer will be needed via License Manager at any time.
As stated above, SVP can be used to increase video frames up to 60/120/144+ fps. For game lovers, video frame game is within easy rich, especially for 120 fps video and 144 fps video. If you want to capture frames from video, turn to video frame grabbers or video frame capture.
Is SVP the best video interpolation software to increase video frames for smooth playback? Not exactly! With the wide application of Artificial Intelligence (AI) in all walks of life, AI-driven algorithms can be used to create video frame interpolation, much more powerful than traditional video interpolation techniques. Move on to the next part that discusses the best SVP alternative.
While SVP is liked by users, it still fades next to AI-driven video interpolation software. In the core of video frame interpolation, we find another vision task named Optical Flow, which is, in a broad sense, understanding how things are moving in an image, at the pixel level. It is useful for a number of downstream video editing tasks, such as video analysis, image stabilization, and video alignment. As we know, an image is comprised of many pixels, and when we move our camera around there is some kind of change happening in these pixels. Optical Flow tries to figure out how that motion affects each individual pixel.
But that's another story. Our focus here is on two modern AI-driven techniques that are applied to conduct video frame interpolation. That is RIFE video interpolation and DAIN video interpolation.
RIFE, short for Real-Time Intermediate Flow Estimation, adopt a neural network named IFNet that can directly estimate the intermediate flows from images. It makes great contributions to Video Frame Interpolation (VFI) based on the below aspects.
The design of a novel and efficient network architecture designed to simplifies the flow-based VFI methods. Thus, given two input frames, the proposed model can be trained from scratch and directly approximate the intermediate flows.
A novel leakage distillation loss function that leads to a more stable convergence and large performance improvement.
The first flow-based real-time VFI algorithm that can process 720p videos at 30fps.
Simply put, video frame interpolation intelligently produces missing video frames between the original ones to enhance the video’s quality and resolution. To expand the scope of AI development services, Oodles AI explores how deep learning-powered video optimization can improve customer experience across business channels. Against such backdrops, Depth-Aware Video Frame Interpolation (DAIN) model comes into being.
Oodles develops a depth-aware flow projection layer to synthesize intermediate flows that preferably sample closer objects than farther ones. DAIN algorithm is the joint effort of Google, UC Merced, and Shanghai Jiao Tong University, a depth-aware video frame interpolation algorithm that can seamlessly generate slow-motion videos from existing content without introducing excessive noise and unwanted artifacts.
Technical speaking, the DAIN model learns about the hierarchal features by collecting contextual information from neighboring pixels in each frame. For synthesizing the output frames, the tool wraps the input frames along with depth maps, and contextual features based on the optical flow and local interpolation kernels. The model can efficiently enhance a video’s quality and temporal resolution by raising the rate of frames to as much as 60 per second. It comprises five submodules, namely the Flow Estimation, Depth Estimation, Context Extraction, Kernel Estimation, and Frame Synthesis Networks. Armed with colorization techniques, the DAIN tool can sharpen and smooth the visuals and eliminate the blurriness in old video clips so as to provide an immersive visual experience.
Similar to other machine learning solutions like image upscaling and voice cloning, this AI-driven video frame interpolation mechanism is attracting lots of attention across verticals to maximize user experience. Since it can provide optimum engagement and immersive visual experience, the DAIN model is widely used to create slow-motion videos and automated animation.
How does DAIN work for slo-mo video?
It is known to all that Slo-Mo is an emerging Computer Vision technique intended for interpolating video frames to create smooth and high-resolution video streams. With the AI-driven video interpolation, DAIN churns the frame rate and resolution from the corresponding low-resolution and low frame rate video frames. Thus, slow-motion videos using AI-driven video frame interpolation are far-reaching including sports, research, cinema, video games, and more.
How does DAIN work for automated animation?
Animated designs, including 2D and 3D animations, are widely applied across industries from movies, cartoons to branding and advertisement. The immediate benefits of improving animation quality cover optimum engagement and impact that eventually upturns a brand’s viewership and profitability. Besides, animation with AI-driven video frame interpolation has vast scope for automating high-resolution marketing campaigns for businesses in diverse industries. 3D product demonstrations and video content are increasingly flourishing among e-Commerce portals to boost customer satisfaction and brand loyalty.
As stated above, RIFE video interpolation and DAIN interpolation are far more powerful than SVP when it comes to improving video frames. Is there any professional AI video interpolations software that adopts RIFE or DAIN to boost video frame rate on the market?
When speaking of Ai-driven video interpolation software in the market, you shall never miss out on DVDFab Smoother AI, the most professional but easiest-to-use tool to increase video frame from any rate to 60 fps.
Now let's check its feature highlights as below.
- Boost video frame rate automatically with AI tech
- Apply to movies, TV shows, animation, sports videos, and more
- Increase video frame rate up to 60 fps for better viewing
- Fast processing speed supported by GPU H/W acceleration
- Change video frame with multi AI Interpolation engines: RIFE & DAIN
- Work with DVDFab DVD/Blu-ray Ripper & Video Converter
- Save files for playback on any device whenever you like
- Free download available on Windows only
With Smoother AI program, your video will be boosted from low frame rate to higher one so that the resulting video will become clearer, sharper, and smoother. If you love watching animation, action movies or sports events, this tool might be your lucky star! Here are 3 simple steps towards how to use this AI-powered video interpolation software to enhance video quality by increasing video frame rate.
- Just run DVDFab 12 and choose Ripper module
- Load your Blu-ray movie source and choose output profile (Smoother AI)\
- Wait for the output file for better playback
Note that DVD Ripper and Video Converter will be supported soon. Act now to have a try, which will bring you unexpected results!
In this post, you have understood SVP's meaning, what video frame interpolation means, the best frame rate for video, and the best SVP alternative driven by AI algorithms like RIFE and DAIN. Next time when you plan to increase the video frames for a better visual experience, do not miss out on such AI-powered techniques. Different from SVP, RIFE and DAIN can automatically improve video frames while producing better image quality. Why not give it a try to improve your video quality via video frame interpolation?