TutorialsVideoFrame Interpolation Deep Dive
AdvancedUpdated Dec 13, 2025

Frame Interpolation Deep Dive

Create smooth slow-motion effects and increase video frame rates using AI-powered frame interpolation with RIFE and optical flow.

DMW
Dr. Marcus Webb
ML Research Lead
15 min read

What is Frame Interpolation?

Frame interpolation generates new frames between existing ones, enabling:

  • Frame rate conversion (24fps → 60fps)
  • Smooth slow motion without artifacts
  • Video quality enhancement

How It Works

Traditional video at 24fps shows 24 images per second. AI interpolation can:

  1. Analyze motion between frames
  2. Predict intermediate positions
  3. Generate new frames
  4. Create smoother playback

Basic Frame Interpolation

python
from abstrakt import AbstraktClient

client = AbstraktClient()

result = client.run("fal-ai/frame-interpolation", {
    "input": {
        "video_url": "https://example.com/original.mp4",
        "target_fps": 60,
        "model": "rife"
    }
})

print(f"Interpolated video: {result.video.url}")

Interpolation Models

RIFE (Real-time Intermediate Flow Estimation)

  • Best for: General purpose
  • Quality: Excellent
  • Speed: Fast

Optical Flow

  • Best for: Simple motion
  • Quality: Good
  • Speed: Very fast

Frame Blending

  • Best for: Quick results
  • Quality: Basic
  • Speed: Instant
python
# RIFE - Best quality
{"model": "rife", "target_fps": 60}

# Optical flow - Balanced
{"model": "optical_flow", "target_fps": 60}

# Blend - Fastest
{"model": "blend", "target_fps": 60}

Creating Slow Motion

Slow motion combines interpolation with playback speed reduction:

python
def create_slow_motion(video_url, slowdown_factor=4):
    """
    Create slow motion video.
    slowdown_factor=4 means 4x slower playback
    """
    
    # First, interpolate to higher fps
    interpolated = client.run("fal-ai/frame-interpolation", {
        "input": {
            "video_url": video_url,
            "multiplier": slowdown_factor,  # 4x more frames
            "model": "rife"
        }
    })
    
    # The video will play at original fps but with 4x frames
    # resulting in 4x slower motion
    return interpolated.video.url

Frame Rate Conversions

Common conversions:

OriginalTargetUse Case
24fps30fpsUS broadcast
24fps60fpsGaming/sports
30fps60fpsSmooth playback
60fps120fpsHigh-end displays
24fps240fpsSlow motion

Quality Settings

python
# Standard quality - faster
{
    "input": {
        "video_url": "...",
        "target_fps": 60,
        "quality": "standard"
    }
}

# High quality - slower but better
{
    "input": {
        "video_url": "...",
        "target_fps": 60,
        "quality": "high",
        "denoise": True
    }
}

Handling Artifacts

Common artifacts and solutions:

Ghosting

Motion blur from fast movement

  • Solution: Use RIFE model, reduce multiplier

Warping

Distortion in complex scenes

  • Solution: Lower target FPS, use optical flow

Edge flickering

Inconsistent edges between frames

  • Solution: Enable denoising, use high quality mode

Batch Processing Videos

python
async def interpolate_batch(video_urls, target_fps=60):
    tasks = []
    
    for url in video_urls:
        task = client.run_async("fal-ai/frame-interpolation", {
            "input": {
                "video_url": url,
                "target_fps": target_fps
            }
        })
        tasks.append(task)
    
    results = await asyncio.gather(*tasks)
    return [r.video.url for r in results]

Performance Tips

  1. Start with 2x - Test before going higher
  2. Check source quality - Bad input = bad output
  3. Consider file size - More frames = larger files
  4. Use appropriate model - RIFE for quality, blend for speed
  5. Process in chunks - For very long videos

Complete Example

python
from abstrakt import AbstraktClient
import asyncio

client = AbstraktClient()

async def enhance_video(video_url):
    # Step 1: Interpolate to 60fps
    interpolated = await client.run_async("fal-ai/frame-interpolation", {
        "input": {
            "video_url": video_url,
            "target_fps": 60,
            "model": "rife",
            "quality": "high"
        }
    })
    
    print(f"Enhanced video: {interpolated.video.url}")
    print(f"Original: 24fps → New: 60fps")
    
    return interpolated.video.url

# Run
url = asyncio.run(enhance_video("https://example.com/video.mp4"))

Next Steps

#video#frame-interpolation#slow-motion#rife
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