Search Results for author:
Found 13 papers, 6 papers with code
EthioLLM: Multilingual Large Language Models for Ethiopian Languages with Task Evaluation
We open-source our multilingual language models, new benchmark datasets for various downstream tasks, and task-specific fine-tuned language models and discuss the performance of the models.
ESPT: A Self-Supervised Episodic Spatial Pretext Task for Improving Few-Shot Learning
With this definition, the ESPT-augmented FSL objective promotes learning more transferable feature representations that capture the local spatial features of different images and their inter-relational structural information in each input episode, thus enabling the model to generalize better to new categories with only a few samples.
SSAT: A Symmetric Semantic-Aware Transformer Network for Makeup Transfer and Removal
Makeup transfer is not only to extract the makeup style of the reference image, but also to render the makeup style to the semantic corresponding position of the target image.
Benchmark Platform for Ultra-Fine-Grained Visual Categorization Beyond Human Performance
The proposed UFG image dataset and evaluation protocols is intended to serve as a benchmark platform that can advance research of visual classification from approaching human performance to beyond human ability, via facilitating benchmark data of artificial intelligence (AI) not to be limited by the labels of human intelligence (HI).
Scene Text Detection with Selected Anchor
Object proposal technique with dense anchoring scheme for scene text detection were applied frequently to achieve high recall.
Multi-components System for Automatic Arabic Diacritization
In this paper, we propose an approach to tackle the problem of the automatic restoration of Arabic diacritics that includes three components stacked in a pipeline: a deep learning model which is a multi-layer recurrent neural network with LSTM and Dense layers, a character-level rule-based corrector which applies deterministic operations to prevent some errors, and a word-level statistical corrector which uses the context and the distance information to fix some diacritization issues.
Ranked #5 on
Arabic Text Diacritization
on Tashkeela
Local Facial Makeup Transfer via Disentangled Representation
In this paper, we propose a novel unified adversarial disentangling network to further decompose face images into four independent components, i. e., personal identity, lips makeup style, eyes makeup style and face makeup style.
Patchy Image Structure Classification Using Multi-Orientation Region Transform
To address above limitations, this paper proposes a novel Multi-Orientation Region Transform (MORT), which can effectively characterize both contour and structure features simultaneously, for patchy image structure classification.
From Species to Cultivar: Soybean Cultivar Recognition using Multiscale Sliding Chord Matching of Leaf Images
Encouraging experimental results of the proposed method in comparison to the state-of-the-art leaf species recognition methods demonstrate the availability of cultivar information in soybean leaves and effectiveness of the proposed MSCM for soybean cultivar identification, which may advance the research in leaf recognition from species to cultivar.
MobileFAN: Transferring Deep Hidden Representation for Face Alignment
To this end, we propose an effective lightweight model, namely Mobile Face Alignment Network (MobileFAN), using a simple backbone MobileNetV2 as the encoder and three deconvolutional layers as the decoder.
Directional Regularized Tensor Modeling for Video Rain Streaks Removal
Outdoor videos sometimes contain unexpected rain streaks due to the rainy weather, which bring negative effects on subsequent computer vision applications, e. g., video surveillance, object recognition and tracking, etc.
Robust Facial Landmark Localization Based on Texture and Pose Correlated Initialization
In this paper, we propose a Robust Initialization for Cascaded Pose Regression (RICPR) by providing texture and pose correlated initial shapes for the testing face.
Word Embeddings and Convolutional Neural Network for Arabic Sentiment Classification
Moreover, a convolutional neural network trained on top of pre-trained Arabic word embeddings is used for sentiment classification to evaluate the quality of these word embeddings.
