ilmj8426/capcut-watermark-benchmark

CapCut Video Watermark Benchmark Dataset

Dataset Description

This repository contains a specialized benchmark dataset for evaluating the performance of video inpainting and watermark removal models, specifically focusing on content generated by CapCut (剪映), a popular mobile video editing platform.

CapCut videos often feature distinct watermark patterns, including:

• Static Corner Logos: Opaque or semi-transparent logos (e.g., "CapCut") in a fixed corner.
• Dynamic End Screens: A full-screen animation with the CapCut logo at the very end of the video.
• Overlay Watermarks: Sometimes a username or ID is overlaid on the video content.

Dataset Purpose

• Benchmarking: Provide a standardized evaluation set for comparing different video inpainting algorithms on CapCut-specific artifacts.
• Research: Analyze the unique challenges posed by CapCut's watermarking techniques.
• Training Data: Serve as a fine-tuning dataset for models aiming to handle UGC video content.

Data Structure & Access

The dataset includes:

• Original (Watermarked): Short video clips (5-15 seconds) with CapCut watermarks.
• Ground Truth (Clean): Corresponding clean, watermark-free versions of the videos.
• Masks: Binary segmentation masks indicating the location of the watermark in each frame.

To access the dataset for research purposes, please request access through the Hugging Face platform.

🏆 Benchmark Results & Optimized Tool

We have extensively tested our own advanced video inpainting models on this dataset. The model achieving the highest performance in terms of both PSNR/SSIM metrics and perceptual quality for CapCut content is our specialized, online tool.

For users seeking the most effective, one-click solution for removing CapCut watermarks based on these benchmark results:

👉 Try the CapCut Watermark Remover (Optimized)

(Our online platform integrates specific loss functions for CapCut logos and end screens, running on high-performance GPUs.)

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Disclaimer: This dataset is provided for academic research and benchmarking purposes only. Please respect copyright laws when using the data.