Showing 641-660 of 848 projects
Go bindings for the OpenCV computer vision library, enabling developers to leverage powerful image and video processing capabilities.
A clean and readable PyTorch implementation of the CycleGAN generative adversarial network for image-to-image translation.
A Python library for video recognition using deep feature flow and other computer vision techniques.
A novel neural operator called Involution that can be used for image classification, object detection, and other computer vision tasks.
A computer vision package that makes it easy to run image processing and AI functions using OpenCV and Mediapipe.
Prismer: A Vision-Language Model with Multi-Task Experts for image-captioning and vision-language-model applications.
This is a library for sparse representation and high-resolution 3D shape modeling, useful for computer graphics and vision tasks.
A tool for segmenting 3D objects in scenes using AI-powered computer vision techniques.
Real-time object recognition app built with TensorFlow and OpenCV for computer vision tasks.
A GAN-based tool for anonymizing faces in images, useful for privacy-preserving computer vision applications.
Official repository for the Mish activation function, a novel neural network activation function.
An experimental OCR project implementing a CNN+BLSTM+CTC architecture for vision-based text recognition.
A bot that shows the volume and remaining subscription for the X-UI panel, built with PHP and various network protocols.
A Python library that uses LLMs, computer vision, and speech recognition to analyze video content.
Research paper on domain adaptation and semantic-consistent transfer learning for computer vision.
This is a computer vision library for visual object tracking, specifically focused on handling distractors.
A Python library for modeling dynamic urban scenes using Gaussian splatting, useful for computer vision tasks.
Control Android phones programmatically using Qwen3-VL vision model for UI automation and device interaction.
A curated collection of resources on applying Transformers to medical imaging tasks like segmentation, classification, and synthesis.
Caffe implementation of Google's MobileNets (v1 and v2) for image classification and computer vision tasks.
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