https://github.com/zbwxp/SegVit
공식 코드SegViT: Semantic Segmentation with Plain Vision Transformers
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SegViT: Semantic Segmentation with Plain Vision Transformers
Non-Iterative Scribble-Supervised Learning with Pacing Pseudo-Masks for Medical Image Segmentation
UniUSNet: A Promptable Framework for Universal Ultrasound Disease Prediction and Tissue Segmentation
Small but Mighty: Enhancing 3D Point Clouds Semantic Segmentation with U-Next Framework
Joint Learning of Saliency Detection and Weakly Supervised Semantic Segmentation
Context Label Learning: Improving Background Class Representations in Semantic Segmentation
Joint Optimization of Class-Specific Training- and Test-Time Data Augmentation in Segmentation
COB-GS: Clear Object Boundaries in 3DGS Segmentation Based on Boundary-Adaptive Gaussian Splitting
Syllable-aware Neural Language Models: A Failure to Beat Character-aware Ones
DVIS++: Improved Decoupled Framework for Universal Video Segmentation
Representation Compensation Networks for Continual Semantic Segmentation
CEDNet: A Cascade Encoder-Decoder Network for Dense Prediction
CEDNet: A Cascade Encoder-Decoder Network for Dense Prediction
CircleFormer: Circular Nuclei Detection in Whole Slide Images with Circle Queries and Attention
OpenMaskDINO3D : Reasoning 3D Segmentation via Large Language Model
Two-Stream Graph Convolutional Network for Intra-oral Scanner Image Segmentation
CarveMix: A Simple Data Augmentation Method for Brain Lesion Segmentation
A Foundation Model for Brain Lesion Segmentation with Mixture of Modality Experts
Boundary-aware Contrastive Learning for Semi-supervised Nuclei Instance Segmentation
DAWN: Domain-Adaptive Weakly Supervised Nuclei Segmentation via Cross-Task Interactions
PointScatter: Point Set Representation for Tubular Structure Extraction
LiDAR-Camera Panoptic Segmentation via Geometry-Consistent and Semantic-Aware Alignment
Temporal-aware Hierarchical Mask Classification for Video Semantic Segmentation
Cross-modal Cognitive Consensus guided Audio-Visual Segmentation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.