6 citations · 9 across the 5 of their papers we have counts for
6 papers · 1 filter
Expose Camouflage in the Water: Underwater Camouflaged Instance Segmentation and Dataset
Chuhong Wang, Hua Li, Chongyi Li +3
With the development of underwater exploration and marine protection, underwater vision tasks are widespread. Due to the degraded underwater environment, characterized by color dis…
WaterFlow: Explicit Physics-Prior Rectified Flow for Underwater Saliency Mask Generation
Runting Li, Shijie Lian, Hua Li +3
Underwater Salient Object Detection (USOD) faces significant challenges, including underwater image quality degradation and domain gaps. Existing methods tend to ignore the physica…
Advancing Marine Research: UWSAM Framework and UIIS10K Dataset for Precise Underwater Instance Segmentation
Hua Li, Shijie Lian, Zhiyuan Li +5
With recent breakthroughs in large-scale modeling, the Segment Anything Model (SAM) has demonstrated significant potential in a variety of visual applications. However, due to the…
TUGS: Physics-based Compact Representation of Underwater Scenes by Tensorized Gaussian
Shijie Lian, Ziyi Zhang, Hua Li +4
Underwater 3D scene reconstruction is crucial for multimedia applications in adverse environments, such as underwater robotic perception and navigation. However, the complexity of…
Evaluation of Segment Anything Model 2: The Role of SAM2 in the Underwater Environment
Shijie Lian, Hua Li
With breakthroughs in large-scale modeling, the Segment Anything Model (SAM) and its extensions have been attempted for applications in various underwater visualization tasks in ma…
Diving into Underwater: Segment Anything Model Guided Underwater Salient Instance Segmentation and A Large-scale Dataset
Shijie Lian, Ziyi Zhang, Hua Li +4
With the breakthrough of large models, Segment Anything Model (SAM) and its extensions have been attempted to apply in diverse tasks of computer vision. Underwater salient instance…