170 citations · 468 across the 48 of their papers we have counts for
48 papers
Asynchrony-Robust Collaborative Perception via Bird's Eye View Flow
Sizhe Wei, Yuxi Wei, Yue Hu +4
Collaborative perception can substantially boost each agent's perception ability by facilitating communication among multiple agents. However, temporal asynchrony among agents is i…
UniBrain: Universal Brain MRI Diagnosis with Hierarchical Knowledge-enhanced Pre-training
Jiayu Lei, Lisong Dai, Haoyun Jiang +9
Magnetic resonance imaging~(MRI) have played a crucial role in brain disease diagnosis, with which a range of computer-aided artificial intelligence methods have been proposed. How…
Bag of Tricks for Long-Tailed Multi-Label Classification on Chest X-Rays
Feng Hong, Tianjie Dai, Jiangchao Yao +2
Clinical classification of chest radiography is particularly challenging for standard machine learning algorithms due to its inherent long-tailed and multi-label nature. However, f…
Balanced Destruction-Reconstruction Dynamics for Memory-replay Class Incremental Learning
Yuhang Zhou, Jiangchao Yao, Feng Hong +2
Class incremental learning (CIL) aims to incrementally update a trained model with the new classes of samples (plasticity) while retaining previously learned ability (stability). T…
Multi-scale Cross-restoration Framework for Electrocardiogram Anomaly Detection
Aofan Jiang, Chaoqin Huang, Qing Cao +5
Electrocardiogram (ECG) is a widely used diagnostic tool for detecting heart conditions. Rare cardiac diseases may be underdiagnosed using traditional ECG analysis, considering tha…
Joint-Relation Transformer for Multi-Person Motion Prediction
Qingyao Xu, Weibo Mao, Jingze Gong +5
Multi-person motion prediction is a challenging problem due to the dependency of motion on both individual past movements and interactions with other people. Transformer-based meth…
Multi-Scale Memory Comparison for Zero-/Few-Shot Anomaly Detection
Chaoqin Huang, Aofan Jiang, Ya Zhang +1
Anomaly detection has gained considerable attention due to its broad range of applications, particularly in industrial defect detection. To address the challenges of data collectio…
Towards Generalist Foundation Model for Radiology by Leveraging Web-scale 2D&3D Medical Data
Chaoyi Wu, Xiaoman Zhang, Ya Zhang +2
In this study, we aim to initiate the development of Radiology Foundation Model, termed as RadFM. We consider the construction of foundational models from three perspectives, namel…
Class-Balancing Diffusion Models
Yiming Qin, Huangjie Zheng, Jiangchao Yao +2
Diffusion-based models have shown the merits of generating high-quality visual data while preserving better diversity in recent studies. However, such observation is only justified…
Boost Video Frame Interpolation via Motion Adaptation
Haoning Wu, Xiaoyun Zhang, Weidi Xie +2
Video frame interpolation (VFI) is a challenging task that aims to generate intermediate frames between two consecutive frames in a video. Existing learning-based VFI methods have…
Zero-shot Composed Text-Image Retrieval
Yikun Liu, Jiangchao Yao, Ya Zhang +2
In this paper, we consider the problem of composed image retrieval (CIR), it aims to train a model that can fuse multi-modal information, e.g., text and images, to accurately retri…
Prompt-Tuning Decision Transformer with Preference Ranking
Shengchao Hu, Li Shen, Ya Zhang +1
Prompt-tuning has emerged as a promising method for adapting pre-trained models to downstream tasks or aligning with human preferences. Prompt learning is widely used in NLP but ha…
PMC-VQA: Visual Instruction Tuning for Medical Visual Question Answering
Xiaoman Zhang, Chaoyi Wu, Ziheng Zhao +4
Medical Visual Question Answering (MedVQA) presents a significant opportunity to enhance diagnostic accuracy and healthcare delivery by leveraging artificial intelligence to interp…
PMC-LLaMA: Towards Building Open-source Language Models for Medicine
Chaoyi Wu, Weixiong Lin, Xiaoman Zhang +3
Recently, Large Language Models (LLMs) have showcased remarkable capabilities in natural language understanding. While demonstrating proficiency in everyday conversations and quest…
Multi-modal Prompting for Low-Shot Temporal Action Localization
Chen Ju, Zeqian Li, Peisen Zhao +5
In this paper, we consider the problem of temporal action localization under low-shot (zero-shot & few-shot) scenario, with the goal of detecting and classifying the action instanc…
DR2: Diffusion-based Robust Degradation Remover for Blind Face Restoration
Zhixin Wang, Xiaoyun Zhang, Ziying Zhang +4
Blind face restoration usually synthesizes degraded low-quality data with a pre-defined degradation model for training, while more complex cases could happen in the real world. Thi…
DiffusionSeg: Adapting Diffusion Towards Unsupervised Object Discovery
Chaofan Ma, Yuhuan Yang, Chen Ju +5
Learning from a large corpus of data, pre-trained models have achieved impressive progress nowadays. As popular generative pre-training, diffusion models capture both low-level vis…
PMC-CLIP: Contrastive Language-Image Pre-training using Biomedical Documents
Weixiong Lin, Ziheng Zhao, Xiaoman Zhang +4
Foundation models trained on large-scale dataset gain a recent surge in CV and NLP. In contrast, development in biomedical domain lags far behind due to data scarcity. To address t…
K-Diag: Knowledge-enhanced Disease Diagnosis in Radiographic Imaging
Chaoyi Wu, Xiaoman Zhang, Yanfeng Wang +2
In this paper, we consider the problem of disease diagnosis. Unlike the conventional learning paradigm that treats labels independently, we propose a knowledge-enhanced framework,…
Constraint and Union for Partially-Supervised Temporal Sentence Grounding
Chen Ju, Haicheng Wang, Jinxiang Liu +5
Temporal sentence grounding aims to detect the event timestamps described by the natural language query from given untrimmed videos. The existing fully-supervised setting achieves…
Long-Tailed Partial Label Learning via Dynamic Rebalancing
Feng Hong, Jiangchao Yao, Zhihan Zhou +2
Real-world data usually couples the label ambiguity and heavy imbalance, challenging the algorithmic robustness of partial label learning (PLL) and long-tailed learning (LT). The s…
Knowledge-enhanced Visual-Language Pre-training on Chest Radiology Images
Xiaoman Zhang, Chaoyi Wu, Ya Zhang +2
While multi-modal foundation models pre-trained on large-scale data have been successful in natural language understanding and vision recognition, their use in medical domains is s…
Open-vocabulary Object Segmentation with Diffusion Models
Ziyi Li, Qinye Zhou, Xiaoyun Zhang +3
The goal of this paper is to extract the visual-language correspondence from a pre-trained text-to-image diffusion model, in the form of segmentation map, i.e., simultaneously gene…
MedKLIP: Medical Knowledge Enhanced Language-Image Pre-Training in Radiology
Chaoyi Wu, Xiaoman Zhang, Ya Zhang +2
In this paper, we consider enhancing medical visual-language pre-training (VLP) with domain-specific knowledge, by exploiting the paired image-text reports from the radiological da…