Add Vivid; Remove enhancr (unmaintained) from FAQ

Removed enhancr entry from the FAQ section. Vivid successes Enhancr

Author: adhityanadooli

docs/faq.md

@@ -26,14 +26,15 @@ There are many programs that can perform AI upscaling, though not all are able t
   - [Download](https://chainner.app/download) | [GitHub](https://github.com/chaiNNer-org/chaiNNer) | [Website](https://chainner.app/)
   - chaiNNer is a node-based image processing GUI that can also be used for image upscaling. It has the most support for models listed on OpenModelDB and can be run with PyTorch (CUDA), ONNX (CUDA), and NCNN (AMD/Intel). Being node based, it allows you to process your images with a lot more control, at the cost of being a bit more complex. Besides upscaling, chaiNNer also has a variety of other use cases and is a very versatile program.
 
+- **Vivid** (closed-source | paid)
+  - [GitHub (Extension SDK)](https://github.com/dusklaboratory/vivid-core)
+  - Desktop AI video processing platform focused on upscaling, frame interpolation, and restoration. It supports multiple runtimes including TensorRT, NCNN, DirectML, CoreML, and ONNX Runtime, enabling efficient processing across NVIDIA, AMD, Intel, and Apple Silicon hardware. Built-in model hub and custom model support!
+  - Unlike traditional tools, Vivid is built around pipelines and queue-based workflows, allowing users to chain operations like upscaling, interpolation, and restoration into a single process. It also supports optional cloud acceleration for significantly faster processing when local hardware is insufficient.
+
 - **AnimeJaNaiConverterGui** (open-source | free)
   - [GitHub](https://github.com/the-database/AnimeJaNaiConverterGui)
   - Allows for fast video upscaling utilizing TensorRT (On Nvidia cards), DirectML, or NCNN within a clean GUI. Only supports ONNX. Use chaiNNer to convert PyTorch models to ONNX for usage.
 
-- **enhancr** (open-source | paid)
-  - [GitHub](https://github.com/mafiosnik777/enhancr)
-  - Meant for fast video frame upscaling and interpolation, enhancr takes advantage of Nvidia's TensorRT to provide fast processing on video. It supports a variety of models, including many of the custom ESRGAN ones from OpenModelDB.
-
 - **VSGAN-TensorRT-docker** (open-source | free)
   - [GitHub](https://github.com/styler00dollar/VSGAN-tensorrt-docker)
   - A more complicated but free alternative for fast video upscaling with TensorRT. Supports an insane amount of models, but requires manual parameter selection.