1 citations · 1 across the 12 of their papers we have counts for
12 papers
SAMOT: State-Aware Step Modulation and Optimal Transport Matching for Audio-Visual Instance Segmentation
Kai Peng, Yunzhe Shen, Miao Zhang +5
Audio-Visual Instance Segmentation (AVIS) aims to simultaneously classify, segment, and track sounding objects within video sequences. Unlike Audio-Visual Semantic Segmentation (AV…
Hear to See: Discerning Stateful Listening for Audio-Visual Instance Segmentation
Leiye Liu, Miao Zhang, Jiahong Jiang +7
Audio-visual instance segmentation (AVIS) requires accurately identifying and tracking individual sounding objects with pixel-level masks. Existing methods struggle to match overla…
AdaSurvMamba: Dynamic Fusion and Semantic Scanning for Multimodal Survival Analysis
Jialong Zhong, Tingwei Liu, Baokun Yue +7
Multimodal survival analysis utilizing whole slide images (WSIs) and genomic profiles is fundamental for cancer prognosis. Recently, state-space models like Mamba have emerged as p…
Text as Illumination: Spatial Contrastive Retinex Learning for Language-guided Medical Image Segmentation
Jian Shi, Cheng Zhen, Pingping Zhang +6
Language-guided Medical Image Segmentation (LMIS) has shown great potential to improve the delineation of anatomical structures and lesions by integrating clinical textual informat…
Towards Large Model Feature Coding
Youwei Pang, Changsheng Gao, Dong Liu +2
Large models have delivered remarkable performance across a wide range of perception and generation tasks, yet practical deployment is increasingly constrained by computational and…
Selective Noise Suppression and Discriminative Mutual Interaction for Robust Audio-Visual Segmentation
Kai Peng, Yunzhe Shen, Miao Zhang +6
The ability to capture and segment sounding objects in dynamic visual scenes is crucial for the development of Audio-Visual Segmentation (AVS) tasks. While significant progress has…
SAM3-I: Segment Anything with Instructions
Jingjing Li, Yue Feng, Yuchen Guo +10
Segment Anything Model 3 (SAM3) advances open-vocabulary segmentation through promptable concept segmentation, enabling users to segment all instances associated with a given conce…
Frequency-Domain Decomposition and Recomposition for Robust Audio-Visual Segmentation
Yunzhe Shen, Kai Peng, Leiye Liu +6
Audio-visual segmentation (AVS) plays a critical role in multimodal machine learning by effectively integrating audio and visual cues to precisely segment objects or regions within…
P3Net: Progressive and Periodic Perturbation for Semi-Supervised Medical Image Segmentation
Zhenyan Yao, Miao Zhang, Lanhu Wu +4
Perturbation with diverse unlabeled data has proven beneficial for semi-supervised medical image segmentation (SSMIS). While many works have successfully used various perturbation…
DefMamba: Deformable Visual State Space Model
Leiye Liu, Miao Zhang, Jihao Yin +4
Recently, state space models (SSM), particularly Mamba, have attracted significant attention from scholars due to their ability to effectively balance computational efficiency and…
CNN-Transformer Rectified Collaborative Learning for Medical Image Segmentation
Lanhu Wu, Miao Zhang, Yongri Piao +4
Automatic and precise medical image segmentation (MIS) is of vital importance for clinical diagnosis and analysis. Current MIS methods mainly rely on the convolutional neural netwo…
CriDiff: Criss-cross Injection Diffusion Framework via Generative Pre-train for Prostate Segmentation
Tingwei Liu, Miao Zhang, Leiye Liu +4
Recently, the Diffusion Probabilistic Model (DPM)-based methods have achieved substantial success in the field of medical image segmentation. However, most of these methods fail to…