RoboTidy : A 3D Gaussian Splatting Household Tidying Benchmark for Embodied Navigation and Action

Dental3R is a new method for intraoral 3D reconstruction that addresses the limitations of traditional intraoral scanning, which is often inaccessible for remote tele-orthodontics. Conventional techniques struggle with sparse smartphone imagery due to large view baselines, inconsistent lighting, and reflective surfaces, leading to challenges in pose and geometry estimation. Dental3R utilizes a pose-free, graph-guided approach to achieve robust, high-fidelity reconstructions from sparse intraoral photographs, overcoming issues like frequency bias that can result in loss of diagnostic details.

Sparse-view synthesis presents challenges in accurately recovering geometry and appearance from limited observations. Recent advancements in 3D Gaussian Splatting (3DGS) have improved real-time rendering quality, yet existing methods often depend on Structure-from-Motion (SfM) for camera pose estimation, which is ineffective in sparse-view scenarios. The proposed Segmentation-Driven Initialization for Gaussian Splatting (SDI-GS) addresses these inefficiencies by utilizing region-based segmentation to focus on structurally significant areas, allowing for effective downsampling of dense point cl…

The paper presents a novel approach to modeling hand-object interactions in dynamic scenes without relying on object priors. It introduces interaction-aware hand-object Gaussians with optimizable parameters to improve structural representation. The method incorporates hand shape into the object deformation field to model flexible motions and employs a progressive optimization strategy to address challenges in dynamic regions and static backgrounds.

Image-Based Gaussian Splatting (IBGS) is a novel approach to 3D Gaussian Splatting (3DGS) that enhances novel view synthesis (NVS) by utilizing high-resolution source images. This method addresses limitations in capturing spatially varying colors and view-dependent effects, such as specular highlights, which are often hindered by low-degree spherical harmonics. By modeling pixel colors as a combination of base colors and learned residuals from neighboring images, IBGS promotes accurate surface alignment and enables the rendering of high-frequency details.