11 citations · 18 across the 4 of their papers we have counts for
4 papers
A Training-Free Framework for Video License Plate Tracking and Recognition with Only One-Shot
Haoxuan Ding, Qi Wang, Junyu Gao +1
Traditional license plate detection and recognition models are often trained on closed datasets, limiting their ability to handle the diverse license plate formats across different…
SamLP: A Customized Segment Anything Model for License Plate Detection
Haoxuan Ding, Junyu Gao, Yuan Yuan +1
With the emergence of foundation model, this novel paradigm of deep learning has encouraged many powerful achievements in natural language processing and computer vision. There are…
The CLIP Model is Secretly an Image-to-Prompt Converter
Yuxuan Ding, Chunna Tian, Haoxuan Ding +1
The Stable Diffusion model is a prominent text-to-image generation model that relies on a text prompt as its input, which is encoded using the Contrastive Language-Image Pre-Traini…
Don't Stop Learning: Towards Continual Learning for the CLIP Model
Yuxuan Ding, Lingqiao Liu, Chunna Tian +2
The Contrastive Language-Image Pre-training (CLIP) Model is a recently proposed large-scale pre-train model which attracts increasing attention in the computer vision community. Be…