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20222025
most citedSkinSAM: Empowering Skin Cancer Segmentation with Segment Anything Model

44 citations · 122 across the 13 of their papers we have counts for

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5 papers · 1 filter

cs.CV2025

Context Matters: Learning Global Semantics via Object-Centric Representation

Jike Zhong, Yuxiang Lai, Xiaofeng Yang +1

Recent advances in language modeling have witnessed the rise of highly desirable emergent capabilities, such as reasoning and in-context learning. However, vision models have yet t…

cs.CV20251 cited

Hunyuan3D Studio: End-to-End AI Pipeline for Game-Ready 3D Asset Generation

Biwen Lei, Yang Li, Xinhai Liu +97

The creation of high-quality 3D assets, a cornerstone of modern game development, has long been characterized by labor-intensive and specialized workflows. This paper presents Huny…

cs.CV202344 cited

SkinSAM: Empowering Skin Cancer Segmentation with Segment Anything Model

Mingzhe Hu, Yuheng Li, Xiaofeng Yang

Skin cancer is a prevalent and potentially fatal disease that requires accurate and efficient diagnosis and treatment. Although manual tracing is the current standard in clinics, a…

cs.CV202320 cited

Advancing Medical Imaging with Language Models: A Journey from N-grams to ChatGPT

Mingzhe Hu, Shaoyan Pan, Yuheng Li +1

In this paper, we aimed to provide a review and tutorial for researchers in the field of medical imaging using language models to improve their tasks at hand. We began by providing…

cs.CV20221 cited

Reinforcement Learning in Medical Image Analysis: Concepts, Applications, Challenges, and Future Directions

Mingzhe Hu, Jiahan Zhang, Luke Matkovic +2

Motivation: Medical image analysis involves tasks to assist physicians in qualitative and quantitative analysis of lesions or anatomical structures, significantly improving the acc…