3D rendering has seen continuous innovation over the years, with new techniques constantly pushing the boundaries of what’s possible. One of the latest advancements making waves is Gaussian splatting—a method that simplifies rendering while delivering stunning visual quality.
This technique is gaining traction among 3D artists and developers, especially those working in software like Blender, where efficiency and realism go hand in hand. Gaussian splatting allows for smoother, more detailed real-time rendering, reducing computational strain while maintaining high fidelity. Given the increasing complexity of modern rendering projects, many professionals rely on Blender Render Farms to optimize performance and accelerate render times.
In this article, we take a closer look at what Gaussian splatting is, how it works, and why it’s becoming a key player in modern rendering techniques.
Gaussian splatting is a radiance field reconstruction technique built on rasterization, designed to facilitate real-time rendering. It uses Gaussian distributions to represent 3D objects as smooth, overlapping points instead of polygons. This unique approach simplifies rendering, making it perfect for real-time applications and handling complex datasets.
In the splatting technique, each splat represents a small portion of an object’s surface and is projected directly onto the screen. This projection bypasses the need for computationally expensive geometry calculations, such as triangulation, required by traditional methods. The splats overlap slightly to form a coherent surface, with their size, shape, and blending properties determining the final visual output.
An advanced variation of this method is Gaussian splatting, which uses Gaussian kernels—smooth, bell-shaped distributions—to model points in 3D space. These Gaussian splats, defined by attributes like position, size, color, and opacity, ensure smooth transitions between data points, making them ideal for rendering irregular or dynamic datasets such as point clouds and volumetric simulations with high-quality visuals.
Gaussian splatting offers a novel approach that is faster and more efficient in specific use cases, such as pre-visualization and lightweight scene representation. However, as Gaussian splatting is still quite a new and emerging technology, traditional rendering methods offer other advantages that we can see below:
Gaussian splatting uses lightweight Gaussian kernels that are directly projected onto the image plane, enabling efficient rendering for large-scale scenes. However, it struggles with intricate details, where its performance lags behind mesh-based methods. In contrast, traditional rendering methods, optimized for established pipelines, achieve high efficiency across most applications, particularly with the support of modern hardware acceleration.
Gaussian splatting lacks the support of level of detail (LOD) systems, which results in lower resolution and visible artifacts during close-ups. This limitation makes it less suitable for scenarios requiring high detail or clarity. On the other hand, traditional rendering methods inherently support LOD systems, allowing for greater resolution and detail as the camera moves closer to the object, making it ideal for intricate or close-up shots.
Gaussian splatting currently does not support Physically Based Rendering (PBR) materials. Lighting and shading are baked into the splats during the capture process, limiting the ability to dynamically adjust these elements under different lighting conditions. Traditional rendering, however, fully supports PBR workflows, enabling realistic material details like reflections, roughness, and translucency, with the added advantage of adjustable lighting in real time or during post-processing.
Gaussian splatting faces challenges with integration, often requiring dedicated plugins or add-ons to work within game engines or rendering workflows. The lack of native support makes it less practical for established pipelines. Traditional rendering, by comparison, is widely compatible with industry-standard tools, making it easier to integrate seamlessly into existing workflows.
Gaussian splatting performs particularly well in depicting transparent or thin objects, such as glass or fine details, where traditional meshes often face challenges. On the other hand, traditional rendering excels in scenarios requiring interactivity, physical simulations, and animation. Meshes in traditional workflows can be rigged, skinned, and simulated, making this approach more versatile for dynamic storytelling.
Gaussian splatting is best suited for quick photorealistic scene captures, particularly for pre-visualization, environment scans, or static background elements. It also simplifies the preservation of highlights without requiring texture rework. Traditional rendering, while slower during production, offers unmatched versatility for both static and dynamic elements. It supports character animation, interactive environments, and real-time lighting adjustments, though the need for texture rework to maintain visual fidelity can add to production time.
As Gaussian splatting continues to gain recognition in 3D rendering, it’s essential to understand how it works and why it’s such a powerful tool for modern applications. The process of Gaussian splatting in 3D rendering is as follows:
This is the initial step where real-world objects or scenes are digitized. Typically, a video sequence is used to capture the scene or object from different angles. This can be done using a single camera or multiple cameras as long as every angle of the object or scene is captured. Each camera contributes overlapping views, which are essential for reconstructing depth and spatial relationships to create a 3D structure. The quality and consistency of these captures significantly influence the accuracy of subsequent steps.
In this step, the data from the video sequence is processed to create a point cloud, which is a 3D representation of the scene:
Depth and Geometry: Each point in the cloud corresponds to a specific location in 3D space, reconstructed from the overlapping perspectives of the captured images.
Attributes: Beyond just geometry, each point can include attributes such as color, which represents the scene's surface appearance.
The point cloud is transformed into a Gaussian kernel-based representation:
Smooth Volumetric Representation: Each point is replaced by a Gaussian kernel, which is a soft, volumetric entity that occupies space. These kernels overlap to create a smooth approximation of surfaces.
Encoded Attributes: Each Gaussian kernel stores information about its position, color, opacity, and size. This allows it to contribute to the visual representation of the 3D scene when rendered.
In this step, color and lighting conditions are embedded into the Gaussian splats. The exact lighting conditions at the time of capture are baked into the splats, meaning shadows, highlights, and ambient light/shadows are permanently stored. However, due to the fixed lighting information, relighting would prove to be a challenge.
The Gaussian splats are rendered or projected onto the image plane to recreate the 3D scene. Their smooth overlap creates the illusion of continuous surfaces. The smooth nature of Gaussian splats allows them to approximate fine surface details without requiring heavy geometric computations.
When the Gaussian splats are ready, they can then be integrated into existing workflows for further refinement such being imported to game Engines or VFX pipelines.
Gaussian splatting has revolutionized real-time rendering like in gaming. Its ability to generate high-quality visuals at exceptional speeds makes it ideal for immersive environments where responsiveness is key. Developers are exploring Gaussian splatting's potential in real-time rendering through platforms like Unreal Engine 5 (UE5), where Gaussian splatting demonstrates smooth motion handling in dynamic scenes:
In the world of visual effects and film production, Gaussian splatting provides a powerful tool for creating lifelike props and environments easily. Unlike traditional methods, this approach balances photorealism and computational efficiency, enabling filmmakers to bring visually complex scenes to life while staying within budget and time constraints. In the video below by Spatial Intelligence, they cover some ways on how Gaussian splatting can be applied and its potential in film:
Scientific fields benefit significantly from Gaussian splatting, especially in molecular modeling, astrophysics, and terrain mapping. Its ability to render complex shapes and patterns with high precision allows researchers to visualize intricate data and gain deeper insights into their studies. Other industries such as medical fields, urban planning, archaeology, and environmental monitoring, where accurate 3D representations are critical, may also benefit from Gaussian splatting, such as this endoscopic reconstruction:
Gaussian splatting is highly efficient when dealing with complex 3D datasets because it sidesteps the need to process dense polygonal meshes. Instead of relying on detailed geometric calculations for every vertex or edge, Gaussian splatting approximates the visual data using Gaussian kernels that are lightweight and computationally manageable.
This makes it particularly useful for scenarios like real-time rendering or handling massive point cloud datasets, where traditional rendering methods might struggle due to their higher memory and processing requirements.
Gaussian splatting’s volumetric approach is well-suited for representing thin or complex features such as hair, foliage, or dirt. By approximating these fine details without requiring dense geometry, it allows for the creation of visually rich 3D reconstructions, making it an invaluable tool for achieving realistic and immersive scenes.
One of the most promising aspects of Gaussian splatting is its accessibility. Unlike traditional methods that often require specialized equipment or software, Gaussian splatting can work effectively on consumer-grade devices such as smartphones. This opens the door for independent creators, small studios, and even hobbyists to produce high quality 3D assets and environments without significant financial or technical barriers.
Despite all their advantages and innovations, Gaussian splatting has its limitations as well. One of which is having limited support for existing pipelines. Although the tech is steadily growing, there is still a lack of native support for Gaussian splatting in 3D engines such as Unreal and Unity, without the use of plug-ins.
Gaussian splatting currently also has a lack of dynamic relighting capabilities, as lighting information is baked into the splat at the time of capture. This means scenes cannot be relit in post-production, which is a significant drawback for workflows requiring lighting adjustments.
Additionally, Gaussian splatting does not support level of detail (LOD) management, resulting in insufficient resolution for close-up shots and limiting its use in high-detail scenarios. Physically Based Rendering (PBR) materials are not yet accommodated as well, restricting its ability to achieve realistic surface effects like reflections, roughness, or metallic finishes, which are essential for photorealistic rendering.
But nonetheless, its ability to bridge the gap between efficiency and quality makes it a compelling alternative in modern rendering workflows and can be a huge game changer in the future.
Gaussian splatting isn’t just a technical innovation; it’s a glimpse into the future of 3D rendering. By seamlessly combining efficiency and quality, it opens up new possibilities for creating breathtaking visuals in real time. It is a game-changing innovation in 3D rendering, balancing efficiency and visual quality and pushing the boundaries of what’s possible in digital graphics. As technology continues to evolve, this method holds the promise of unlocking even greater creativity and transforming how we see and interact with digital worlds. The future of 3D graphics has never looked more exciting.
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