The paper introduces a new framework that uses 2D Gaussian Splatting to capture view‑dependent specular effects, especially near‑field reflections, by directly leveraging observable environment information in input images. It combines a hybrid reflection appearance representation with view‑dependent specular modeling, and demonstrates improved rendering quality and geometric accuracy on public benchmarks and a newly curated near‑field reflection dataset.
arXiv:2603. 07664v3 Announce Type: replace-cross Abstract: The reflective appearance, especially strong and typically near-field specular reflections, poses a fundamental challenge for accurate surface reconstruction and novel view synthesis.
Reflections from shiny objects and glass facades naturally extend the field of view of a camera, capturing the surrounding environment without the need to pan the camera or acquire a full panorama. We propose PanoLess, a Gaussian-splat-based framework that reconstructs the surrounding environment as a distant illumination map from images captured on only one side of a reflective surface.
arXiv:2609.37115v1 Announce Type: new Abstract: We revisit the role of appearance modeling in 3D Gaussian Splatting (3DGS) and show that limited expressiveness in view-dependent reflectance is a key...
The paper introduces Reflection-aware Gaussian Splatting (RGS), a physically-based deferred rendering framework that improves novel view synthesis for reflective objects. RGS leverages a powerful 3D foundation model to provide a strong geometric prior and employs cross-view shape consistency regularization to prevent surface collapse and reduce geometric hollows. Additionally, a reflection-aware densification strategy captures specular variations across views, resulting in higher-quality renderings of reflective objects.
GraftRay is a method for inserting mesh objects into scenes reconstructed with 2D or 3D Gaussian splatting, ensuring physically consistent lighting and shadows. It recovers scene materials and normals using diffusion priors, models spatially‑extended emitters in closed form, and employs a hybrid renderer that path‑traces both Gaussians and meshes to produce view‑consistent shading, interreflections, and soft shadows. On the FIPT benchmark, GraftRay achieves state‑of‑the‑art rendering fidelity and shadow accuracy while remaining competitive in rendering efficiency.
arXiv:2610.01876v1 Announce Type: new Abstract: A surface photographed under even light presents nearly the same appearance from every angle; the same surface under uneven light does not. Exposure ch...
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.
arXiv:2606. 05124v1 Announce Type: cross Abstract: After the success of 3D Gaussian Splatting (3DGS) for novel view synthesis, many works have explored how to also use it for geometric surface representation.
The paper introduces TruncGradGS, a piecewise truncated gradient approach that mitigates gradient vanishing in 3D Gaussian Splatting, enhancing optimization stability and robustness to initializations. It demonstrates consistent improvements over random and COLMAP initializations in both static and dynamic settings. Additionally, the authors highlight limitations of existing dynamic scene benchmarks and present a new synthetic dataset for evaluating dynamic Gaussian Splatting.
arXiv:2610.19847v1 Announce Type: new Abstract: We address inverse rendering with 3D Gaussian Splatting (3DGS) by introducing explicit visibility modeling for relighting as well as material and light...
arXiv:2603.20714v4 Announce Type: replace Abstract: 3D Gaussian Splatting (3DGS) has become the method of choice for photo-realistic novel view synthesis (NVS), due to its efficiency and compelling v...
The paper introduces Camera Splatting, a novel framework for optimizing camera viewpoints in novel view synthesis. Each camera is represented as a 3D Gaussian (camera splat), and virtual point cameras are positioned near the surface to sample the distribution of these splats. By continuously refining the camera splats to match desired target distributions observed from the point cameras, the method achieves better capture of complex view‑dependent effects such as metallic reflections and detailed textures compared to the Farthest View Sampling approach.