48 citations · 58 across the 9 of their papers we have counts for
6 papers · 1 filter
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…
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…
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)…