17 citations · 47 across the 9 of their papers we have counts for
15 papers
Imagine yourself: Tuning-Free Personalized Image Generation
Zecheng He, Bo Sun, Felix Juefei-Xu +14
Diffusion models have demonstrated remarkable efficacy across various image-to-image tasks. In this research, we introduce Imagine yourself, a state-of-the-art model designed for p…
Learning from Children: Improving Image-Caption Pretraining via Curriculum
Hammad A. Ayyubi, Rahul Lokesh, Alireza Zareian +2
Image-caption pretraining has been quite successfully used for downstream vision tasks like zero-shot image classification and object detection. However, image-caption pretraining…
GOCA: Guided Online Cluster Assignment for Self-Supervised Video Representation Learning
Huseyin Coskun, Alireza Zareian, Joshua L. Moore +2
Clustering is a ubiquitous tool in unsupervised learning. Most of the existing self-supervised representation learning methods typically cluster samples based on visually dominant…
SGEITL: Scene Graph Enhanced Image-Text Learning for Visual Commonsense Reasoning
Zhecan Wang, Haoxuan You, Liunian Harold Li +5
Answering complex questions about images is an ambitious goal for machine intelligence, which requires a joint understanding of images, text, and commonsense knowledge, as well as…
Open-Vocabulary Object Detection Using Captions
Alireza Zareian, Kevin Dela Rosa, Derek Hao Hu +1
Despite the remarkable accuracy of deep neural networks in object detection, they are costly to train and scale due to supervision requirements. Particularly, learning more object…
Unsupervised Vision-and-Language Pre-training Without Parallel Images and Captions
Liunian Harold Li, Haoxuan You, Zhecan Wang +3
Pre-trained contextual vision-and-language (V&L) models have achieved impressive performance on various benchmarks. However, existing models require a large amount of parallel imag…