Showing 41-60 of 116 projects
An open-source library for multilingual automatic speech recognition with word-level timestamps and confidence.
Official PyTorch implementation of U-GAT-IT, an unsupervised generative adversarial network for image-to-image translation.
Dual Attention Network for Scene Segmentation, a computer vision model for image segmentation.
CodeSearchNet provides datasets, tools, and benchmarks for representation learning of code, enabling AI-powered code discovery.
A framework for generating realistic human images using a Liquid Warping GAN with Attention.
A PyTorch implementation of various Unet models for image segmentation, including Attention Unet and Nested Unet.
A powerful BERT-based language model for natural language understanding and representation learning.
Official PyTorch implementation for a novel method to visualize classifications by Transformer based networks.
A comprehensive survey of text classification algorithms and techniques in Python.
Official PyTorch implementation of the TimeSformer model for video understanding.
A comprehensive set of Keras-based NLP models for text classification, similarity, and more, with support for Chinese and English.
Experimental spaced repetition platform for exploring ideas in memory augmentation and programmable attention
A repository of machine learning and Tensorflow deep learning models for natural language processing problems.
A PyTorch implementation of the YOLOv4 object detection model with support for various attention mechanisms and mobile models.
This is a Python library for learning flow fields in attention for controllable person image generation.
Examples of using sparse attention, a technique for efficient Transformer-based sequence modeling.
A PyTorch implementation of the BiDAF network for question-answering on the SQuAD dataset.
A high-performance AI-powered image super-resolution and restoration library for computer vision tasks.
PyTorch code for image super-resolution using very deep residual channel attention networks
Non-official implementation of the CBAM paper, a convolutional block attention module for neural networks.
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