46 citations · 167 across the 72 of their papers we have counts for
11 papers · 1 filter
Large-Vocabulary Segmentation for Medical Images with Text Prompts
Ziheng Zhao, Yao Zhang, Chaoyi Wu +5
This paper aims to build a model that can Segment Anything in 3D medical images, driven by medical terminologies as Text prompts, termed as SAT. Our main contributions are three-fo…
Large-scale Long-tailed Disease Diagnosis on Radiology Images
Qiaoyu Zheng, Weike Zhao, Chaoyi Wu +7
Developing a generalist radiology diagnosis system can greatly enhance clinical diagnostics. In this paper, we introduce RadDiag, a foundational model supporting 2D and 3D inputs a…
Multi-Sentence Grounding for Long-term Instructional Video
Zeqian Li, Qirui Chen, Tengda Han +3
In this paper, we aim to establish an automatic, scalable pipeline for denoising the large-scale instructional dataset and construct a high-quality video-text dataset with multiple…
UniChest: Conquer-and-Divide Pre-training for Multi-Source Chest X-Ray Classification
Tianjie Dai, Ruipeng Zhang, Feng Hong +3
Vision-Language Pre-training (VLP) that utilizes the multi-modal information to promote the training efficiency and effectiveness, has achieved great success in vision recognition…
Uncovering Prototypical Knowledge for Weakly Open-Vocabulary Semantic Segmentation
Fei Zhang, Tianfei Zhou, Boyang Li +6
This paper studies the problem of weakly open-vocabulary semantic segmentation (WOVSS), which learns to segment objects of arbitrary classes using mere image-text pairs. Existing w…
Combating Representation Learning Disparity with Geometric Harmonization
Zhihan Zhou, Jiangchao Yao, Feng Hong +3
Self-supervised learning (SSL) as an effective paradigm of representation learning has achieved tremendous success on various curated datasets in diverse scenarios. Nevertheless, w…
Redundancy-Adaptive Multimodal Learning for Imperfect Data
Mengxi Chen, Jiangchao Yao, Linyu Xing +3
Multimodal models trained on complete modality data often exhibit a substantial decrease in performance when faced with imperfect data containing corruptions or missing modalities.…
Can GPT-4V(ision) Serve Medical Applications? Case Studies on GPT-4V for Multimodal Medical Diagnosis
Chaoyi Wu, Jiayu Lei, Qiaoyu Zheng +8
Driven by the large foundation models, the development of artificial intelligence has witnessed tremendous progress lately, leading to a surge of general interest from the public.…
Boundary-aware Supervoxel-level Iteratively Refined Interactive 3D Image Segmentation with Multi-agent Reinforcement Learning
Chaofan Ma, Qisen Xu, Xiangfeng Wang +4
Interactive segmentation has recently been explored to effectively and efficiently harvest high-quality segmentation masks by iteratively incorporating user hints. While iterative…
Latent Class-Conditional Noise Model
Jiangchao Yao, Bo Han, Zhihan Zhou +2
Learning with noisy labels has become imperative in the Big Data era, which saves expensive human labors on accurate annotations. Previous noise-transition-based methods have achie…
Integrating features from lymph node stations for metastatic lymph node detection
Chaoyi Wu, Feng Chang, Xiao Su +4
Metastasis on lymph nodes (LNs), the most common way of spread for primary tumor cells, is a sign of increased mortality. However, metastatic LNs are time-consuming and challenging…