1 citations · 2 across the 6 of their papers we have counts for
6 papers
Efficient Visual Question Answering Pipeline for Autonomous Driving via Scene Region Compression
Yuliang Cai, Dongqiangzi Ye, Zitian Chen +1
Autonomous driving increasingly relies on Visual Question Answering (VQA) to enable vehicles to understand complex surroundings by analyzing visual inputs and textual queries. Curr…
TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP
Yuliang Cai, Jesse Thomason, Mohammad Rostami
Vision-language models (VLMs), such as CLIP, have demonstrated strong performance across a range of downstream tasks. However, CLIP is still limited in negation understanding: the…
CluMo: Cluster-based Modality Fusion Prompt for Continual Learning in Visual Question Answering
Yuliang Cai, Mohammad Rostami
Large vision-language models (VLMs) have shown significant performance boost in various application domains. However, adopting them to deal with several sequentially encountered ta…
Enhancing Bandwidth Efficiency for Video Motion Transfer Applications using Deep Learning Based Keypoint Prediction
Xue Bai, Tasmiah Haque, Sumit Mohan +4
We propose a deep learning based novel prediction framework for enhanced bandwidth reduction in motion transfer enabled video applications such as video conferencing, virtual reali…
Dynamic Transformer Architecture for Continual Learning of Multimodal Tasks
Yuliang Cai, Mohammad Rostami
Transformer neural networks are increasingly replacing prior architectures in a wide range of applications in different data modalities. The increasing size and computational deman…
Task-Attentive Transformer Architecture for Continual Learning of Vision-and-Language Tasks Using Knowledge Distillation
Yuliang Cai, Jesse Thomason, Mohammad Rostami
The size and the computational load of fine-tuning large-scale pre-trained neural network are becoming two major obstacles in adopting machine learning in many applications. Contin…