Awesome GitHub RepositoriesVideo Sequence Preprocessing

LivePortrait is a deep learning framework for portrait animation that transfers facial expressions from a driving video to a static image. It functions as an AI motion retargeting tool, mapping movements between different identities while preserving the unique features of the source portrait. The system includes specialized capabilities for cross-species portrait animation, adapting human-centric models to non-human subjects and animals. It also features a motion template generator that converts driving videos into portable files to accelerate inference and protect the identity of the origina

mmagic is a multimodal training pipeline and framework for generative AI, focusing on visual synthesis and restoration. It provides the infrastructure to build and train models for tasks such as text-to-image and text-to-video generation, 3D-aware content synthesis, and high-fidelity image translation using diffusion models and generative adversarial networks. The project distinguishes itself through specialized capabilities for generative model personalization, including techniques for fine-tuning subjects and styles. It also supports advanced visual manipulations such as latent space interp

LatentSync एक ऑडियो-ड्रिवन वीडियो जनरेटर और लेटेंट डिफ़्यूज़न लिप सिंक मॉडल है जिसे वीडियो में स्पीकर के होंठों की गतिविधियों को टारगेट ऑडियो ट्रैक के साथ सिंक्रोनाइज़ करने के लिए डिज़ाइन किया गया है। यह कस्टम वीडियो और ऑडियो डेटासेट पर सिंक्रोनाइज़ेशन नेटवर्क विकसित करने के लिए एक लिप सिंक्रोनाइज़ेशन ट्रेनिंग फ़्रेमवर्क प्रदान करता है। यह सिस्टम फेस डेटा को साफ़ करने, सेगमेंट करने और संरेखित करने के लिए एक वीडियो प्रीप्रोसेसिंग पाइपलाइन का उपयोग करता है। इसमें एक विज़ुअल सिंक मूल्यांकन टूल शामिल है जो जेनरेट किए गए वीडियो में ऑडियो और विज़ुअल संरेखण की सटीकता को मापने के लिए कॉन्फ़िडेंस स्कोर की गणना करता है। यह प्रोजेक्ट कस्टम सिंक्रोनाइज़ेशन नेटवर्क विकास, हार्डवेयर मेमोरी और रिज़ॉल्यूशन के लिए ट्रेनिंग कॉन्फ़िगरेशन मैनेजमेंट और सिंथेटिक वीडियो मूल्यांकन के लिए क्षमताओं को कवर करता है।

This project is a PyTorch implementation of 3D residual networks designed for video action recognition. It provides a spatiotemporal architecture that analyzes both spatial frames and temporal motion to classify human activities within video clips. The system includes a distributed model training framework to accelerate learning across multiple compute nodes. It supports the deployment and fine-tuning of pre-trained model weights, allowing the adaptation of existing networks to specific new datasets. The codebase covers the full pipeline for spatiotemporal learning, including video dataset p

FastVideo is a comprehensive system for accelerated video generation, serving as a video generation inference engine, a video diffusion training framework, and a modular pipeline orchestrator. It provides a distributed transformer optimizer and a distillation toolkit designed to reduce denoising steps and model complexity to increase frame rates. The project distinguishes itself through specialized acceleration techniques, including joint distillation and sparse attention training. It implements low-step video generation and weight quantization to FP8 or FP4 precision to increase throughput a

This project is a computer vision library designed for facial landmark detection and alignment. It provides a framework for identifying and mapping specific points on a human face in both two-dimensional and three-dimensional space, enabling the normalization of facial geometry and orientation across diverse images. The system utilizes a deep learning approach to extract precise facial coordinates, supporting tasks such as expression analysis and geometric modeling. By employing a stacked hourglass architecture, the model performs multi-stage feature refinement to capture spatial relationship