Search Results for author:
Found 6 papers, 2 papers with code
Medical Visual Prompting (MVP): A Unified Framework for Versatile and High-Quality Medical Image Segmentation
This novel framework offers improved performance with fewer parameters and holds significant potential for accurate segmentation of lesion regions in various medical tasks, making it clinically valuable.
Adaptive Query Prompting for Multi-Domain Landmark Detection
Thanks to the lightweight nature of the decoder and AQP, we can handle multiple datasets by sharing the backbone encoder and then only perform partial parameter tuning without incurring much additional cost.
Rotate to Scan: UNet-like Mamba with Triplet SSM Module for Medical Image Segmentation
Image segmentation holds a vital position in the realms of diagnosis and treatment within the medical domain.
QEAN: Quaternion-Enhanced Attention Network for Visual Dance Generation
The study of music-generated dance is a novel and challenging Image generation task.
RBA-GCN: Relational Bilevel Aggregation Graph Convolutional Network for Emotion Recognition
This module can construct the interaction between different modalities and capture long-range contextual information based on similarity clusters.
Quaternion-valued Correlation Learning for Few-Shot Semantic Segmentation
In this paper, we introduce a quaternion perspective on correlation learning and propose a novel Quaternion-valued Correlation Learning Network (QCLNet), with the aim to alleviate the computational burden of high-dimensional correlation tensor and explore internal latent interaction between query and support images by leveraging operations defined by the established quaternion algebra.
Ranked #19 on
Few-Shot Semantic Segmentation
on COCO-20i (5-shot)
