intro-skipper — Automatic Intro and Credits Detection
Description
Jellyfin plugin that detects intro and credit sequences using Chromaprint audio matching plus silence and black-frame analyzers, emitting standard media segments.
Resource details
- Category path
- Media Tools›Scene Detection & Segmentation
- Classification
- Not yet classified
intro-skipper — Automatic Intro and Credits Detection is cataloged in Media Tools and Scene Detection & Segmentation.
URL
Related resources
- MDLSeg: Parameter-Free Video Scene Segmentation via Minimum Description LengthAcademic paper proposing a parameter-free scene-segmentation method claimed to outperform PySceneDetect.
- SceneSegmentation-SCRLOfficial PyTorch implementation of CVPR 2022 Scene Consistency Representation Learning for movie-level scene segmentation (MovieNet/SceneSe…
- SpectroMap: Peak Detection Algorithm for Audio FingerprintingAcademic paper on a peak-detection algorithm for audio fingerprinting with implementation.
- SparseSync: Audio-Visual Synchronisation with Trainable SelectorsBMVC 2022 Spotlight paper and code for sparse-in-space-and-time audio-visual sync detection.
- Eyevinn auto-subtitlesWhisper-based automatic subtitle generation tool that chunks large audio and outputs VTT/SRT/JSON while preserving sync.
- Evaluating Video Quality Metrics for Neural and Traditional Codecs (4K/UHD-1)Academic comparison of VMAF, AVQBits, and FasterVQA no-reference quality metrics on 4K content.
- Bitrate Ladder Construction via Transfer Learning and Spatio-Temporal FeaturesML-based bitrate ladder optimization achieving 94.1% complexity reduction at only 1.71% BD-rate cost using transfer learning.
- VMAF-torchPyTorch reimplementation of VMAF metric, GPU/gradient-friendly for use in learned codec optimization loops.
- CompressedVQA: Full/No-Reference VQA for Compressed UGC VideoICME 2021 grand challenge-winning full-reference and no-reference video quality models for compressed user-generated content.
- 2BiVQA: Double Bi-LSTM No-Reference Video Quality AssessmentNo-reference VQA model for UGC video using double Bi-LSTM, companion code to arXiv:2208.14774.