2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.LG2024★ 1 cited
AutoM3L: An Automated Multimodal Machine Learning Framework with Large Language Models
Daqin Luo, Chengjian Feng, Yuxuan Nong +1
Automated Machine Learning (AutoML) offers a promising approach to streamline the training of machine learning models. However, existing AutoML frameworks are often limited to unim…
cs.CV2024★ 2 cited
OV-DINO: Unified Open-Vocabulary Detection with Language-Aware Selective Fusion
Hao Wang, Pengzhen Ren, Zequn Jie +8
Open-vocabulary detection is a challenging task due to the requirement of detecting objects based on class names, including those not encountered during training. Existing methods…
cs.CV2024
InstaGen: Enhancing Object Detection by Training on Synthetic Dataset
Chengjian Feng, Yujie Zhong, Zequn Jie +2
In this paper, we present a novel paradigm to enhance the ability of object detector, e.g., expanding categories or improving detection performance, by training on synthetic datase…