COREA: Coarse-to-Fine 3D Representation Alignment Between Relightable 3D Gaussians and SDF via Bidirectional 3D-to-3D Supervision

arXiv — cs.CVWednesday, December 10, 2025 at 5:00:00 AM
  • COREA has been introduced as a pioneering framework that integrates relightable 3D Gaussians and Signed Distance Fields (SDF) to enhance geometry reconstruction and relighting accuracy. This approach employs a coarse-to-fine bidirectional alignment strategy, allowing for improved geometric signal learning directly in 3D space, addressing limitations seen in previous 3D Gaussian Splatting methods.
  • The development of COREA is significant as it promises to overcome the challenges of coarse surfaces and unreliable BRDF-lighting decomposition that have hindered the effectiveness of existing 3D reconstruction techniques. By stabilizing Gaussian growth and balancing geometric fidelity with memory efficiency, COREA sets a new standard in the field.
  • This advancement reflects a broader trend in the AI and computer vision sectors, where enhancing 3D Gaussian Splatting techniques is crucial for applications in real-time rendering and novel view synthesis. The integration of methods like LiDAR-assisted densification and view alignment further emphasizes the ongoing efforts to refine 3D representation and improve rendering quality in various contexts.
— via World Pulse Now AI Editorial System

Was this article worth reading? Share it

Recommended apps based on your readingExplore all apps
Continue Readings
Zero-Splat TeleAssist: A Zero-Shot Pose Estimation Framework for Semantic Teleoperation
NeutralArtificial Intelligence
The introduction of Zero-Splat TeleAssist presents a zero-shot sensor-fusion pipeline that converts standard CCTV streams into a shared, six-degree-of-freedom world model for teleoperation. This innovative framework integrates various technologies, including vision-language segmentation and 3D Gaussian Splatting, enabling operators to access real-time positions and orientations of multiple robots without the need for fiducials or depth sensors.
Visionary: The World Model Carrier Built on WebGPU-Powered Gaussian Splatting Platform
PositiveArtificial Intelligence
Visionary has been introduced as an open, web-native platform utilizing WebGPU technology to enhance real-time rendering of 3D Gaussian Splatting (3DGS) and meshes. This platform addresses the limitations of existing viewer solutions, which are often heavy and constrained by outdated pipelines, thereby facilitating a more dynamic and efficient rendering experience.
On-the-fly Large-scale 3D Reconstruction from Multi-Camera Rigs
PositiveArtificial Intelligence
Recent advancements in 3D Gaussian Splatting (3DGS) have led to the development of an innovative on-the-fly 3D reconstruction framework utilizing multi-camera rigs. This method integrates dense RGB streams from overlapping cameras into a unified Gaussian representation, enabling real-time reconstruction and accurate trajectory estimation without calibration.
ConsDreamer: Advancing Multi-View Consistency for Zero-Shot Text-to-3D Generation
PositiveArtificial Intelligence
The introduction of ConsDreamer marks a significant advancement in zero-shot text-to-3D generation, addressing the multi-view inconsistencies that arise from prior view biases in text-to-image models. This innovative method incorporates a View Disentanglement Module to refine the score distillation process, enhancing the quality of 3D content creation from textual descriptions.
AGORA: Adversarial Generation Of Real-time Animatable 3D Gaussian Head Avatars
PositiveArtificial Intelligence
AGORA has been introduced as a novel framework that enhances the generation of animatable 3D human avatars by extending 3D Gaussian Splatting within a generative adversarial network. This development addresses the limitations of existing methods, such as slow rendering and lack of dynamic control, enabling real-time inference and fine-grained expression control.
MeshSplatting: Differentiable Rendering with Opaque Meshes
PositiveArtificial Intelligence
MeshSplatting has been introduced as a novel mesh-based reconstruction technique that optimizes geometry and appearance through differentiable rendering, enhancing real-time rendering capabilities in 3D engines. This method improves upon existing point-based representations, specifically addressing the limitations of 3D Gaussian Splatting in applications like AR/VR and gaming.
AdLift: Lifting Adversarial Perturbations to Safeguard 3D Gaussian Splatting Assets Against Instruction-Driven Editing
PositiveArtificial Intelligence
AdLift has been introduced as a pioneering safeguard for 3D Gaussian Splatting (3DGS) assets, addressing the vulnerabilities posed by instruction-driven editing. This method lifts 2D adversarial perturbations into a 3D Gaussian-represented safeguard, ensuring protection against unauthorized edits across various views and dimensions.
TriaGS: Differentiable Triangulation-Guided Geometric Consistency for 3D Gaussian Splatting
PositiveArtificial Intelligence
The paper introduces TriaGS, a novel method for enhancing 3D Gaussian Splatting by enforcing geometric consistency through constrained multi-view triangulation. This approach addresses the limitations of existing methods that rely solely on photometric loss, which can lead to artifacts and unstructured geometry in 3D reconstructions.