Awesome-GANs is a curated resource list and research repository focused on the development and evaluation of generative adversarial networks. It serves as a structured index for academic literature and open-source implementations dedicated to the creation of synthetic data generators. The project provides a framework for training competing neural networks to produce outputs that mimic the statistical properties of original datasets. It emphasizes the use of configuration-driven pipelines to manage model hyperparameters and dataset paths, facilitating reproducible research workflows and standa
CARLA is an autonomous driving simulator and research environment designed for developing and validating self-driving software. It functions as an urban traffic simulator that generates realistic vehicle and pedestrian behavior and as a synthetic sensor data generator producing LiDAR, Radar, and camera data. The platform distinguishes itself through its deep integration with robotics frameworks, specifically providing native connectivity to ROS2 nodes for robotic control and data processing. It supports the training of driving models via imitation and reinforcement learning within a controlle
manga-ocr is a Japanese OCR engine and text extraction tool designed to recognize vertical and horizontal Japanese text from manga images. It operates as a vision encoder-decoder model that converts visual text into digital characters. The project includes an OCR training pipeline and a synthetic data generator. These tools create artificial image-text pairs by overlaying diverse Japanese text fonts onto background images to refine recognition models. The system provides automation for extracting text by monitoring the system clipboard or directories. This allows for the conversion of manga
jetson-inference is a set of libraries and tools for executing optimized deep learning models on embedded GPU hardware. Its primary purpose is to enable real-time computer vision and AI inference at the edge with low latency and high throughput. The project distinguishes itself through high-performance streaming analytics and the ability to execute concurrent AI pipelines on auto-grade silicon. It provides specialized support for multi-sensor stream processing, utilizing zero-copy data transport to load camera frames directly into GPU memory. The codebase covers a broad surface of capabiliti
This repository contains the code for our ACL 2023 paper Event Extraction as Question Generation and Answering .
The main features of dataminr-ai/event-extraction-as-question-generation-and-answering are: Event Extraction, Synthetic Data Generation.
Open-source alternatives to dataminr-ai/event-extraction-as-question-generation-and-answering include: kozistr/awesome-gans — Awesome-GANs is a curated resource list and research repository focused on the development and evaluation of… carla-simulator/carla — CARLA is an autonomous driving simulator and research environment designed for developing and validating self-driving… kha-white/manga-ocr — manga-ocr is a Japanese OCR engine and text extraction tool designed to recognize vertical and horizontal Japanese… dusty-nv/jetson-inference — jetson-inference is a set of libraries and tools for executing optimized deep learning models on embedded GPU… facebookresearch/habitat-sim — Habitat-sim is a high-performance 3D simulation platform designed for training and benchmarking embodied AI agents… lexfridman/mit-deep-learning — This project is a collection of deep learning courseware and instructional materials. It provides a structured…