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[2025-1] 박서형 - How far are we from solving the 2D & 3D Face Alignment problem? (and adataset of 230,000 3D facial landmarks) https://arxiv.org/abs/1703.07332 How far are we from solving the 2D & 3D Face Alignment problem? (and a dataset of 230,000 3D facial landmarks)This paper investigates how far a very deep neural network is from attaining close to saturating performance on existing 2D and 3D face alignment datasets. To this end, we make the following 5 contributions: (a) we construct, for the first time, a very st.. 2025. 4. 5.
[2025-1] 유경석 - PMC-VQA: Visual Instruction Tuning for Medical Visual Question Answering https://arxiv.org/pdf/2305.10415v6  AbstractMedVQA를 생성(generative) 문제로 재구성하여 인간-기계 상호작용을 자연스럽게 구현Pre-trained vision encoder와 LLM을 결합한 생성 기반 모델 제안PMC-VQA dataset 구축 : Image - Q&A pair로 구성된 VQA로 다양한 medical modality를 다룸Model 성능 평가 : PMC-VQA에서 훈련 후 VQA-RAD, SLAKE, Image-Clef-2019 benchmark에서 fine-tunning, 기존 MedVQA 모델보다 더 정확하고 적절한 답변 생성.Test set 제시 : manual verification을 거친 새로운 test set 제안하여 모델 성능을.. 2025. 4. 5.
[2025-1] 주서영 - Enabling Text-free Inference in Language-guided Segmentation of Chest X-rays via Self-guidance Enabling Text-free Inference in Language-guided Segmentation of Chest X-rays via Self-guidance Enabling Text-free Inference in Language-guided Segmentation of Chest X-rays via Self-guidance11institutetext: The University of Sydney Enabling Text-free Inference in Language-guided Segmentation of Chest X-rays via Self-guidance Shuchang Ye    Mingyuan Meng    Mingjian Li    Dagan Feng    Jinman Kim .. 2025. 4. 5.
[2025-1] 전연주 - Textmatch: Using Text Prompts to Improve Semisupervised Medical Image Segmentation 논문 링크: [2412.18185] TextMatch: Enhancing Image-Text Consistency Through Multimodal Optimization TextMatch: Enhancing Image-Text Consistency Through Multimodal OptimizationText-to-image generative models excel in creating images from text but struggle with ensuring alignment and consistency between outputs and prompts. This paper introduces TextMatch, a novel framework that leverages multimodal o.. 2025. 4. 4.