paper-with-me

Papers

AquaFuse: Waterbody Fusion for Physics Guided View Synthesis of Underwater Scenes

2024-11-02 · Md Abu Bakr Siddique, Jiayi Wu, Ioannis Rekleitis, Md Jahidul Islam

We introduce the idea of AquaFuse, a physics-based method for synthesizing waterbody properties in underwater imagery. We formulate a closed-form solution for waterbody fusion that facilitates realistic data augmentation and geometrically consistent underwater scene rendering. AquaFuse leverages the physical characteristics of light propagation underwater to synthesize the waterbody from one scene to the object contents of another. Unlike data-driven style transfer, AquaFuse preserves the depth consistency and object geometry in an input scene. We validate this unique feature by comprehensive experiments over diverse underwater scenes. We find that the AquaFused images preserve over 94% depth consistency and 90-95% structural similarity of the input scenes. We also demonstrate that it generates accurate 3D view synthesis by preserving object geometry while adapting to the inherent waterbody fusion process. AquaFuse opens up a new research direction in data augmentation by geometry-preserving style transfer for underwater imaging and robot vision applications.

📄 PDF Abstract BibTeX arXiv:2411.01119

Code (0)

등록된 구현이 없습니다.

Tasks

Data AugmentationObjectStyle Transfer

Similar Papers 제목 키워드 기반

UStyle: Waterbody Style Transfer of Underwater Scenes by Depth-Guided Feature Synthesis

2025-03-14 · Md Abu Bakr Siddique, Vaishnav Ramesh, Junliang Liu, Piyush Singh 외

The concept of waterbody style transfer remains largely unexplored in the underwater imaging and vision literature. Traditional image style transfer (STx) methods primarily focus on artistic and photorealistic blending, …

Style Transfer

PMA-Diffusion: A Physics-guided Mask-Aware Diffusion Framework for TSE from Sparse Observations

2025-12-05 · Lindong Liu, Zhixiong Jin, Seongjin Choi arxiv

High-resolution highway traffic state information is essential for Intelligent Transportation Systems, but typical traffic data acquired from loop detectors and probe vehicles are often too sparse and noisy to capture th…

FCDM: A Physics-Guided Bidirectional Frequency Aware Convolution and Diffusion-Based Model for Sinogram Inpainting

2024-08-26 · Jiaze E, Srutarshi Banerjee, Tekin Bicer, Guannan Wang 외

Computed tomography (CT) is widely used in industrial and medical imaging, but sparse-view scanning reduces radiation exposure at the cost of incomplete sinograms and challenging reconstruction. Existing RGB-based inpain…

Computed Tomography (CT)CT ReconstructionImage ReconstructionScheduling+1

ATLANTIS: A Benchmark for Semantic Segmentation of Waterbody Images

2021-11-22 · Seyed Mohammad Hassan Erfani, Zhenyao Wu, Xinyi Wu, Song Wang 외

Vision-based semantic segmentation of waterbodies and nearby related objects provides important information for managing water resources and handling flooding emergency. However, the lack of large-scale labeled training …

SegmentationSemantic Segmentation

PhysDiff: Physics-Guided Human Motion Diffusion Model

2022-12-05 · ICCV 2023 1 · Ye Yuan, Jiaming Song, Umar Iqbal, Arash Vahdat 외

Denoising diffusion models hold great promise for generating diverse and realistic human motions. However, existing motion diffusion models largely disregard the laws of physics in the diffusion process and often generat…

Denoisingmodel