48 citations · 58 across the 9 of their papers we have counts for
9 papers
ANetQA: A Large-scale Benchmark for Fine-grained Compositional Reasoning over Untrimmed Videos
Zhou Yu, Lixiang Zheng, Zhou Zhao +4
Building benchmarks to systemically analyze different capabilities of video question answering (VideoQA) models is challenging yet crucial. Existing benchmarks often use non-compos…
Epistemic Graph: A Plug-And-Play Module For Hybrid Representation Learning
Jin Yuan, Yang Zhang, Yangzhou Du +4
In recent years, deep models have achieved remarkable success in various vision tasks. However, their performance heavily relies on large training datasets. In contrast, humans exh…
Multi-task Paired Masking with Alignment Modeling for Medical Vision-Language Pre-training
Ke Zhang, Yan Yang, Jun Yu +4
In recent years, the growing demand for medical imaging diagnosis has placed a significant burden on radiologists. As a solution, Medical Vision-Language Pre-training (Med-VLP) met…
Cross-domain recommendation via user interest alignment
Chuang Zhao, Hongke Zhao, Ming He +2
Cross-domain recommendation aims to leverage knowledge from multiple domains to alleviate the data sparsity and cold-start problems in traditional recommender systems. One popular…
Learning to Learn Domain-invariant Parameters for Domain Generalization
Feng Hou, Yao Zhang, Yang Liu +6
Due to domain shift, deep neural networks (DNNs) usually fail to generalize well on unknown test data in practice. Domain generalization (DG) aims to overcome this issue by capturi…
SAP-DETR: Bridging the Gap Between Salient Points and Queries-Based Transformer Detector for Fast Model Convergency
Yang Liu, Yao Zhang, Yixin Wang +5
Recently, the dominant DETR-based approaches apply central-concept spatial prior to accelerate Transformer detector convergency. These methods gradually refine the reference points…
Self-Supervised Graph Neural Network for Multi-Source Domain Adaptation
Jin Yuan, Feng Hou, Yangzhou Du +4
Domain adaptation (DA) tries to tackle the scenarios when the test data does not fully follow the same distribution of the training data, and multi-source domain adaptation (MSDA)…
Bilaterally Slimmable Transformer for Elastic and Efficient Visual Question Answering
Zhou Yu, Zitian Jin, Jun Yu +3
Recent advances in Transformer architectures [1] have brought remarkable improvements to visual question answering (VQA). Nevertheless, Transformer-based VQA models are usually dee…
Trust It or Not: Confidence-Guided Automatic Radiology Report Generation
Yixin Wang, Zihao Lin, Zhe Xu +7
Medical imaging plays a pivotal role in diagnosis and treatment in clinical practice. Inspired by the significant progress in automatic image captioning, various deep learning (DL)…