1 citations · 2 across the 5 of their papers we have counts for
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TEAMS: Text-prompted spatiotEmporal dual-heAd Mamba Snake
Ruicheng Zhang, Jianhui Lei, Kaiwen Shen +6
Deep snake is a promising family of instance segmentation methods that accurately predicts object-level contours, thereby overcoming common pixel-level misclassification issues suc…
LongCat-Next: Lexicalizing Modalities as Discrete Tokens
Meituan LongCat Team, Bin Xiao, Chao Wang +86
The prevailing Next-Token Prediction (NTP) paradigm has driven the success of large language models through discrete autoregressive modeling. However, contemporary multimodal syste…
MARL-MambaContour: Unleashing Multi-Agent Deep Reinforcement Learning for Active Contour Optimization in Medical Image Segmentation
Ruicheng Zhang, Yu Sun, Zeyu Zhang +5
We introduce MARL-MambaContour, the first contour-based medical image segmentation framework based on Multi-Agent Reinforcement Learning (MARL). Our approach reframes segmentation…
Unified Medical Image Segmentation with State Space Modeling Snake
Ruicheng Zhang, Haowei Guo, Kanghui Tian +4
Unified Medical Image Segmentation (UMIS) is critical for comprehensive anatomical assessment but faces challenges due to multi-scale structural heterogeneity. Conventional pixel-b…
GAMED-Snake: Gradient-aware Adaptive Momentum Evolution Deep Snake Model for Multi-organ Segmentation
Ruicheng Zhang, Haowei Guo, Zeyu Zhang +2
Multi-organ segmentation is a critical yet challenging task due to complex anatomical backgrounds, blurred boundaries, and diverse morphologies. This study introduces the Gradient-…