Search Results for author:
Found 7 papers, 3 papers with code
CheX-GPT: Harnessing Large Language Models for Enhanced Chest X-ray Report Labeling
Moreover, models using expert-annotated data are limited by data scarcity and pre-defined classes, impacting their performance, flexibility and scalability.
Open-Vocabulary Object Detection using Pseudo Caption Labels
Recent open-vocabulary detection methods aim to detect novel objects by distilling knowledge from vision-language models (VLMs) trained on a vast amount of image-text pairs.
DEER: Detection-agnostic End-to-End Recognizer for Scene Text Spotting
Since only a single point is required to recognize the text, the proposed method enables text spotting without an arbitrarily-shaped detector or bounding polygon annotations.
Ranked #7 on
Text Spotting
on Total-Text
HoughCL: Finding Better Positive Pairs in Dense Self-supervised Learning
Compared to previous works, our method shows better or comparable performance on dense prediction fine-tuning tasks.
SynthTIGER: Synthetic Text Image GEneratoR Towards Better Text Recognition Models
For successful scene text recognition (STR) models, synthetic text image generators have alleviated the lack of annotated text images from the real world.
SWAD: Domain Generalization by Seeking Flat Minima
Domain generalization (DG) methods aim to achieve generalizability to an unseen target domain by using only training data from the source domains.
Ranked #25 on
Domain Generalization
on TerraIncognita
BABO: Background Activation Black-Out for Efficient Object Detection
Recent advances in deep learning have enabled complex real-world use cases comprised of multiple vision tasks and detection tasks are being shifted to the edge side as a pre-processing step of the entire workload.
