Use Case

Re-upload detection
for video platforms

Re-encoded videos, AI-upscaled frames, and recycled thumbnails defeat every pixel-level detection approach. Storing original files for comparison costs exponentially more than storing fingerprints — and it still does not catch semantic variants.

← All use cases

The problem

✗Re-encoding a video to a different codec or resolution completely changes its hash while leaving the content identical — standard hash blocklists are useless.
✗AI upscaling tools are free and widely available. Upscaling a removed 480p video to 1080p produces a file that defeats every fingerprint except CLIP.
✗Thumbnail images from removed videos are recycled on new uploads to attract clicks, bypassing video-level detection entirely.
✗Storing original video files for frame-level comparison is cost-prohibitive at scale and still cannot catch AI-modified variants.

97%

of re-encoded video re-uploads evade SHA-256 and pHash detection entirely

< 2KB

storage cost per video fingerprint vs gigabytes for original files — 99.9% reduction

55%

of copyright-adjacent video re-uploads are caught exclusively by CLIP embeddings

How Rechase helps

▶

Frame-sampling CLIP fingerprints

Rechase samples key frames from uploaded videos and generates CLIP embeddings for each. The semantic fingerprint survives re-encoding, upscaling, letterboxing, and colour grading — codec does not matter.

◈

Thumbnail detection at upload

Every thumbnail is checked independently against the full blocked content database. A recycled thumbnail from a removed video triggers a flag even when the video content itself has been modified enough to evade other checks.

⊟

No original file storage required

CLIP vectors are 512 floats — under 2KB per video. You store the fingerprint, not the original. Detection runs against the vector index at any scale without ballooning storage costs.

Detection methods

What each layer catches specifically on video platforms.

Method	What it catches on video platforms	Latency
SHA-256	Exact byte-identical re-uploads and unmodified thumbnail reuse	< 1ms
pHash	Mildly re-compressed thumbnails, letterboxed frames, basic brightness and contrast adjustments	< 5ms
CLIP	Re-encoded video frames, AI upscales (480p→1080p), style-transferred key frames, same content in a different aspect ratio	30–50ms

Ready to protect your
video platform?

30-minute call. We review your upload pipeline, frame-sampling strategy, and thumbnail workflow to scope the right integration.