AI & Machine Learning Tools
Page 2 of 2: Explore 35 curated AI & Machine Learning Tools resources in Media Tools — tools, guides, and references for video developers on Awesome Video.
About this collection
AI & Machine Learning Tools is a focused collection within Media Tools, with 35 curated resources.
Resources
- SwiftVR: Real-Time One-Step Generative Video Restoration2026 paper on real-time one-step diffusion-distillation video restoration, part of emerging real-time generative VSR research line.
- TorchCodec Documentation — FFmpeg-Backed Video Decoding to TensorsMeta's library docs for decoding video/audio directly into PyTorch tensors with CPU and CUDA/NVDEC paths, index- and PTS-based frame access…
- Track-AnythingInteractive video object tracking and segmentation tool built on Segment Anything, XMem, and E2FGVI, feeding video inpainting pipelines.
- TwelveLabs Marengo — Video Embedding Model DocumentationDocs for a multimodal video embedding model supporting long-form video with shot-boundary segmentation, used for search, dedup and content…
- Upscale-A-VideoCVPR 2024 temporal-consistent diffusion model for real-world video super-resolution.
- UpscalerCLI-friendly consolidation of compiled open-source AI image/video upscaler binaries, no Python environment needed.
- VapourSynth Super-Resolution HelperSetup scripts and configurations for running ESRGAN-family super-resolution models inside VapourSynth encoding graphs.
- Video TensorflowTalk deck on using TensorFlow for audience measurement in video streaming pipelines.
- VideocrExtract hardcoded subtitles from videos using machine learning
- genai-video-super-resolutionAWS sample pipeline combining Real-ESRGAN and SwinIR to upscale low-resolution video up to 4x using AWS services.
- mpv-AnimeJaNai — real-time ML upscaling in mpvReal-time 1080p to 4K upscaling inside mpv using compact Real-ESRGAN ONNX models via TensorRT/DirectML and VapourSynth.