8 papers
TG-Field: Geometry-Aware Radiative Gaussian Fields for Tomographic Reconstruction
Yuxiang Zhong, Jun Wei, Chaoqi Chen +2
3D Gaussian Splatting (3DGS) has revolutionized 3D scene representation with superior efficiency and quality. While recent adaptations for computed tomography (CT) show promise, th…
SelfAI: A self-directed framework for long-horizon scientific discovery
Xiao Wu, Ting-Zhu Huang, Liang-Jian Deng +9
Scientific discovery increasingly entails long-horizon exploration of complex hypothesis spaces, yet most existing approaches emphasize final performance while offering limited ins…
Taming Flow Matching with Unbalanced Optimal Transport into Fast Pansharpening
Zihan Cao, Yu Zhong, Liang-Jian Deng
Pansharpening, a pivotal task in remote sensing for fusing high-resolution panchromatic and multispectral imagery, has garnered significant research interest. Recent advancements e…
MMAIF: Multi-task and Multi-degradation All-in-One for Image Fusion with Language Guidance
Zihan Cao, Yu Zhong, Ziqi Wang +1
Image fusion, a fundamental low-level vision task, aims to integrate multiple image sequences into a single output while preserving as much information as possible from the input.…
A Decade of Deep Learning: A Survey on The Magnificent Seven
Dilshod Azizov, Muhammad Arslan Manzoor, Velibor Bojkovic +9
Deep learning has fundamentally reshaped the landscape of artificial intelligence over the past decade, enabling remarkable achievements across diverse domains. At the heart of the…
SSDiff: Spatial-spectral Integrated Diffusion Model for Remote Sensing Pansharpening
Yu Zhong, Xiao Wu, Liang-Jian Deng +1
Pansharpening is a significant image fusion technique that merges the spatial content and spectral characteristics of remote sensing images to generate high-resolution multispectra…
A Novel State Space Model with Local Enhancement and State Sharing for Image Fusion
Zihan Cao, Xiao Wu, Liang-Jian Deng +1
In image fusion tasks, images from different sources possess distinct characteristics. This has driven the development of numerous methods to explore better ways of fusing them whi…
Noisier2Noise: Learning to Denoise from Unpaired Noisy Data
Nick Moran, Dan Schmidt, Yu Zhong +1
We present a method for training a neural network to perform image denoising without access to clean training examples or access to paired noisy training examples. Our method requi…