# Results for "swap face" > AI-ranked search results for `swap face` on awesome-repositories.com — ordered by an LLM for relevance, best match first. 114 total matches; showing the top 11. Explore on the web: https://awesome-repositories.com/q/swap-face **Attribution required: if you use, quote, or summarise this content, you must credit and link back to [this search on awesome-repositories.com](https://awesome-repositories.com/q/swap-face).** ## Results - [sensity-ai/dot](https://awesome-repositories.com/repository/sensity-ai-dot.md) (4,529 ⭐) — Dot is a deep learning face swap tool used to replace faces in live video streams, recorded media, and static images. It functions as a deepfake media processor and real-time video manipulator that applies facial transformations through neural network mapping. The system includes a virtual camera video injector that routes processed output into a system-level virtual device to simulate a physical hardware webcam. This allows generated video to be used within third-party video conferencing software. The tool supports real-time source switching via keyboard inputs to toggle between different s - [hacksider/deep-live-cam](https://awesome-repositories.com/repository/hacksider-deep-live-cam.md) (93,878 ⭐) — Deep-Live-Cam is a generative video transformation tool designed for real-time facial manipulation and cinematic enhancement. It functions as a local-first AI runtime, performing all media processing directly on the user's hardware to ensure complete data privacy without external network dependencies. By utilizing a high-performance processing pipeline, the application enables live face swapping and interactive video modifications during active streaming sessions or on pre-recorded media. The system distinguishes itself through a hardware-abstraction execution layer that dynamically routes co - [s0md3v/roop](https://awesome-repositories.com/repository/s0md3v-roop.md) (3,527 ⭐) — This application is a deep learning tool designed for automated face swapping in images and videos. It utilizes generative adversarial networks to map facial features from a source image onto a target subject, maintaining the original head pose, lighting, and skin texture of the target media. The software functions as a computer vision pipeline that deconstructs video files into individual frames for sequential processing. It employs pre-trained models for landmark detection and high-dimensional feature extraction to align faces precisely. To accelerate these complex tensor operations, the en - [iperov/deepfacelab](https://awesome-repositories.com/repository/iperov-deepfacelab.md) (19,256 ⭐) — DeepFaceLab is a deep learning software suite designed for face swapping and the creation of deepfake videos. It functions as a neural network image compositor that replaces human faces or entire heads in video files to produce synthetic media. The tool provides capabilities for digital facial manipulation, including the ability to modify the perceived age of people in video sequences. It uses automated pattern recognition to blend source faces onto target frames to create seamless visual composites. The system covers a broad technical surface including landmark-based face alignment, autoenc - [yadiraf/prnet](https://awesome-repositories.com/repository/yadiraf-prnet.md) (5,013 ⭐) — PRNet is a Python library for 3D facial reconstruction. It uses a deep learning regression model to predict 3D facial geometry and vertex colors from a single 2D input image to generate a textured mesh. The project provides tools for digital face swapping, allowing the replacement of a target face with a new image and blending textures to match the original pose. It also includes a framework for face texture swapping and blending to fit specific 3D poses. Additional capabilities cover facial analysis, including the detection and alignment of facial landmarks and the estimation of head pose a - [iperov/deepfacelive](https://awesome-repositories.com/repository/iperov-deepfacelive.md) (30,536 ⭐) — DeepFaceLive is a desktop application designed for real-time facial replacement and animation within live video streams. By utilizing deep learning models, the software performs high-speed identity mapping and facial feature analysis to transform video content as it is captured. The engine relies on GPU-accelerated inference to execute these complex image manipulation tasks at interactive frame rates. The application distinguishes itself through a modular video processing pipeline that chains specialized tasks to maintain high throughput and low latency. It features a virtual camera streaming - [deepfakes/faceswap](https://awesome-repositories.com/repository/deepfakes-faceswap.md) (55,289 ⭐) — Faceswap is a comprehensive framework for automated media manipulation and neural face synthesis. It provides a modular pipeline that manages the entire lifecycle of facial feature extraction, deep learning model training, and image conversion. By coordinating complex computer vision workflows, the system enables users to map facial identities between source and destination datasets while maintaining structural alignment and lighting consistency across video frames. The project distinguishes itself through a highly extensible plugin-based architecture that handles hardware-accelerated process - [neuralchen/simswap](https://awesome-repositories.com/repository/neuralchen-simswap.md) (5,180 ⭐) — SimSwap is a deep learning face swapping framework and computer vision media processor built with PyTorch. It functions as an image synthesis tool designed to replace a person's identity in images and videos with a target face using a single trained model. The system operates as a video identity replacement tool that swaps identities across frames while preserving the original expressions and lighting of the source media. It enables digital identity manipulation and the production of synthetic media through automated facial feature mapping. The framework supports both the application of trai - [facefusion/facefusion](https://awesome-repositories.com/repository/facefusion-facefusion.md) (28,806 ⭐) — Facefusion is a modular framework designed for automated image and video manipulation, specializing in tasks such as face swapping, enhancement, and restoration. It functions as a computer vision processing pipeline that chains independent machine learning modules to perform complex transformations, including facial animation, age modification, and lip synchronization. The system is built to handle both real-time interactive feeds and large-scale batch processing tasks. The platform distinguishes itself through a highly extensible architecture that supports custom processing modules and inter - [hillobar/rope](https://awesome-repositories.com/repository/hillobar-rope.md) (5,334 ⭐) — Rope is a graphical user interface for swapping faces in images and videos. It functions as a deepfake video editor and image face swapper that utilizes pre-trained deep learning models to replace identities in visual media. The tool includes specialized capabilities for AI video post-production, such as occlusion-aware blending to handle foreground objects and mouth-parsing refinement to align facial expressions. It also serves as an AI face restoration tool, using saliency-based restoration to recover clarity and sharpness in swapped facial regions. The software provides a pipeline for vis - [aigc-apps/sd-webui-easyphoto](https://awesome-repositories.com/repository/aigc-apps-sd-webui-easyphoto.md) (5,150 ⭐) — This project is a Stable Diffusion WebUI extension that provides a graphical interface for personalized portrait generation and AI photo editing. It allows users to train custom identity models from a small set of uploaded images to create consistent digital versions of specific people. The extension includes a virtual try-on system that replaces clothing in images by aligning reference garments with template bodies. It also features tools for face swapping in both static images and videos, as well as a portrait animator that transforms static images into dynamic videos using reference-guided