Tri‑DehazeGS is a Gaussian Splatting framework that decouples clean scene reconstruction from atmospheric haze by representing the scene with Gaussian primitives and the haze medium with an independent view‑shared tri‑plane field. It uses a physical scattering model to compose hazy observations and introduces Medium‑Decoupled Transmittance Gradient Compensation (MD‑TGC) to re‑balance gradients in low‑transmittance regions without altering forward rendering. Experiments on real and synthetic haze benchmarks demonstrate that this approach improves clean novel‑view reconstruction.
By Kui Jiang, Yang Gu, Jiacheng Liu, Shiyu Liu, Youyu Chen, Hui Liu
Existing diffusion-based methods have recently made significant progress in image dehazing. However, they typically neglect the physics of haze formation and reconstruct clean images from pure Gaussian noise, thereby limiting their restoration potential.
FujinSplat is a method for reconstructing clean 3D scenes from images captured through smoke by operating in the RAW image domain, where the camera’s ISP and the medium’s scattering effects remain separable. It first learns a per‑scene base ISP from hazy RAW captures, then uses a low‑dimensional correction space to fit per‑view corrections at training poses, and finally trains a scene‑agnostic controller to predict these corrections from RAW input. The corrected views supervise a single static 3D Gaussian representation, with a bounded per‑view residual to reconcile cross‑view inconsistencies, achieving superior performance on the RealX3D smoke benchmark compared to physics‑based and restoration‑then‑3DGS baselines.
By Gengjia Chang, Ziteng Cui, Shuhong Liu
DPSF-Net is a dual‑prior spatial‑frequency network designed for real‑world remote sensing image dehazing. It combines hazy RGB images with dark channel prior maps as joint inputs, and incorporates a spatial‑frequency residual interaction block, a prior‑guided feature attention module, and a selective kernel complementary fusion module to reduce colour shift, structural distortion, and large‑scale haze. Experiments show that DPSF-Net achieves state‑of‑the‑art performance on the RRSHID benchmark while maintaining a favorable balance of restoration quality, parameter count, and computational complexity.
By Mei Lu, Shangliang Shao, Shanliang Yao
3D Gaussian Splatting (3DGS) employs Gaussian primitives for explicit scene representation, facilitating real-time, high-fidelity reconstruction and novel view synthesis of complex scenes. However, the explicit modeling inherent in 3DGS introduces a gradient bias during optimization, rendering its non-convex optimization process highly susceptible to convergence toward local suboptimal solutions.
arXiv:2607.05598v2 Announce Type: replace-cross
Abstract: Novel View Synthesis (NVS) methods, such as 3D Gaussian Splatting (3DGS), rely on the assumption of clean, multi-view consistent, posed input...
By Kristof Overdulve, Lode Jorissen, Nick Michiels
arXiv:2604. 13416v2 Announce Type: replace-cross Abstract: Advances in radiance fields have enabled photorealistic novel view synthesis.
By Cheng-You Lu, Yi-Shan Hung, Wei-Ling Chi, Hao-Ping Wang, Charlie Li-Ting Tsai, Yu-Cheng Chang, Yu-Lun Liu, Thomas Do, Chin-Teng Lin
arXiv:2606. 31637v1 Announce Type: cross Abstract: Intrinsic decomposition which expresses image colors as the product of diffuse albedo and shading, possibly augmented with view-dependent residuals has a long history in image editing as it enables the modification of object colors and textures without altering lighting.
By Alexandre Lanvin, Jeffrey Hu, Simon Lucas, Adrien Bousseau, George Drettakis
arXiv:2508.03077v2 Announce Type: replace
Abstract: Feedforward 3D Gaussian Splatting (3DGS) overcomes the limitations of optimization-based 3DGS by enabling fast and high-quality reconstruction with...
By Anran Wu, Long Peng, Xin Di, Xueyuan Dai, Chen Wu, Yang Wang, Xueyang Fu, Yang Cao, Zheng-Jun Zha
arXiv:2609.12682v1 Announce Type: new
Abstract: Reconstructing 3D scenes under real-world low-light conditions remains challenging due to severe sensor noise, low signal-to-noise ratios, and degraded...
By Shaurya Pavan A, Vemunuri Divya Madhuri, Yash Pradeep Gawande, Kaushik Mitra
arXiv:2606. 30049v1 Announce Type: cross Abstract: Visibility distance is critical to maritime navigational safety because it determines the effective observation range of shipborne and shore-based monitoring systems.
By Wentao Feng, Guobei Peng, Wengang Mao, Ryan Wen Liu
arXiv:2506.19445v5 Announce Type: replace
Abstract: Motion blur remains one of the most common and visually disruptive degradations in real-world smartphone imaging, yet existing deblurring benchmark...
By Syed Mumtahin Mahmud, Mahdi Mohd Hossain Noki, Prothito Shovon Majumder, Abdul Mohaimen Al Radi, Sudipto Das Sukanto, Afia Lubaina, Md. Mosaddek Khan