1 citations · 2 across the 17 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…
SC-Diff: Semantically Calibrated Diffusion for Visible-to-Infrared Image Translation
Junyin Zhang, Siyu Huang, Jianxiong Ye +4
Visible-to-infrared image translation provides a practical way to expand infrared training data using abundant visible images. Diffusion models are promising for this task because…
PhysEditWorld: A Large-Scale Dataset Toward Physics-Editable World Models
Bin Hu, Yanwen Ma, Jiehui Huang +14
Recent game world models can synthesize visually plausible, action-conditioned rollouts. However, their interaction behaviors often remain limited to exploratory or wandering traje…
RoboStereo: Dual-Tower 4D Embodied World Models for Unified Policy Optimization
Ruicheng Zhang, Guangyu Chen, Zunnan Xu +5
Scalable Embodied AI faces fundamental constraints due to prohibitive costs and safety risks of real-world interaction. While Embodied World Models (EWMs) offer promise through ima…
Identity-Consistent Video Generation under Large Facial-Angle Variations
Bin Hu, Zipeng Qi, Guoxi Huang +6
Single-view reference-to-video methods often struggle to preserve identity consistency under large facial-angle variations. This limitation naturally motivates the incorporation of…
EditCast3D: Single-Frame-Guided 3D Editing with Video Propagation and View Selection
Huaizhi Qu, Ruichen Zhang, Shuqing Luo +5
Recent advances in foundation models have driven remarkable progress in image editing, yet their extension to 3D editing remains underexplored. A natural approach is to replace the…
Zo3T: Zero-Shot 3D-Aware Trajectory-Guided Image-to-Video Generation via Test-Time Training
Ruicheng Zhang, Jun Zhou, Zunnan Xu +5
Trajectory-Guided image-to-video (I2V) generation aims to synthesize videos that adhere to user-specified motion instructions. Existing methods typically rely on computationally ex…
RPD-Diff: Region-Adaptive Physics-Guided Diffusion Model for Visibility Enhancement under Dense and Non-Uniform Haze
Ruicheng Zhang, Puxin Yan, Zeyu Zhang +3
Single-image dehazing under dense and non-uniform haze conditions remains challenging due to severe information degradation and spatial heterogeneity. Traditional diffusion-based d…
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…
DC-Scene: Data-Centric Learning for 3D Scene Understanding
Ting Huang, Zeyu Zhang, Ruicheng Zhang +1
3D scene understanding plays a fundamental role in vision applications such as robotics, autonomous driving, and augmented reality. However, advancing learning-based 3D scene under…
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-…
TAGE: Trustworthy Attribute Group Editing for Stable Few-shot Image Generation
Ruicheng Zhang, Guoheng Huang, Yejing Huo +4
Generative Adversarial Networks (GANs) have emerged as a prominent research focus for image editing tasks, leveraging the powerful image generation capabilities of the GAN framewor…
Perceptual Similarity guidance and text guidance optimization for Editing Real Images using Guided Diffusion Models
Ruichen Zhang
When using a diffusion model for image editing, there are times when the modified image can differ greatly from the source. To address this, we apply a dual-guidance approach to ma…