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20202026
most citedAttention-based Convolutional Autoencoders for 3D-Variational Data Assimilation

48 citations · 184 across the 24 of their papers we have counts for

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16 papers · 1 filter

cs.CV202616 cited

Accurate identification and measurement of the precipitate area by two-stage deep neural networks in novel chromium-based alloys

Zeyu Xia, Kan Ma, Sibo Cheng +7

The performance of advanced materials for extreme environments is underpinned by their microstructure, including the size and distribution of reinforcing phases. Chromium-based sup…

cs.CV2025

Knowledge to Sight: Reasoning over Visual Attributes via Knowledge Decomposition for Abnormality Grounding

Jun Li, Che Liu, Wenjia Bai +4

In this work, we address the problem of grounding abnormalities in medical images, where the goal is to localize clinical findings based on textual descriptions. While generalist V…

cs.CV2025

How Far Have Medical Vision-Language Models Come? A Comprehensive Benchmarking Study

Che Liu, Jiazhen Pan, Weixiang Shen +3

Vision-Language Models (VLMs) trained on web-scale corpora excel at natural image tasks and are increasingly repurposed for healthcare; however, their competence in medical tasks r…

cs.CV2025

BOTM: Echocardiography Segmentation via Bi-directional Optimal Token Matching

Zhihua Liu, Lei Tong, Xilin He +4

Existed echocardiography segmentation methods often suffer from anatomical inconsistency challenge caused by shape variation, partial observation and region ambiguity with similar…

cs.CV2025

Enhancing Abnormality Grounding for Vision Language Models with Knowledge Descriptions

Jun Li, Che Liu, Wenjia Bai +3

Visual Language Models (VLMs) have demonstrated impressive capabilities in visual grounding tasks. However, their effectiveness in the medical domain, particularly for abnormality…

cs.CV2024

How Does Diverse Interpretability of Textual Prompts Impact Medical Vision-Language Zero-Shot Tasks?

Sicheng Wang, Che Liu, Rossella Arcucci

Recent advancements in medical vision-language pre-training (MedVLP) have significantly enhanced zero-shot medical vision tasks such as image classification by leveraging large-sca…