Differentiable rendering methods promise the ability to optimize various parameters of three-dimensional (3D) scenes to achieve a desired result. However, lighting design has so far received little attention in this field. In this article, we introduce a method that enables continuous optimization of the arrangement of luminaires in a 3D scene via differentiable light tracing. Our experiments show two major issues when attempting to apply existing methods from differentiable path tracing to this problem: First, many rendering methods produce images, which restricts the ability of a designer to define lighting objectives to image space. Second, most previous methods are designed for scene geometry or material optimization and have not been extensively tested for the case of optimizing light sources. Currently available differentiable ray-tracing methods do not provide satisfactory performance, even on fairly basic test cases in our experience. In this article, we propose, to the best of our knowledge, a novel adjoint light tracing method that overcomes these challenges and enables gradient-based lighting design optimization in a view-independent (camera-free) way. Thus, we allow the user to paint illumination targets directly onto the 3D scene or use existing baked illumination data (e.g., light maps). Using modern ray-tracing hardware, we achieve interactive performance. We find light tracing advantageous over path tracing in this setting, as it naturally handles irregular geometry, resulting in less noise and improved optimization convergence. We compare our adjoint gradients to state-of-the-art image-based differentiable rendering methods. We also demonstrate that our gradient data works with various common optimization algorithms, providing good convergence behaviour. Qualitative comparisons with real-world scenes underline the practical applicability of our method.

可微渲染方法有望优化三维 (3D) 场景的各种参数以实现所需的结果。然而，迄今为止，照明设计在这一领域还很少受到关注。在本文中，我们介绍了一种通过可微分光追踪持续优化 3D 场景中灯具排列的方法。我们的实验表明，当尝试将可微路径追踪的现有方法应用于此问题时，存在两个主要问题：首先，许多渲染方法都会生成图像，这限制了设计者将照明目标定义到图像空间的能力。其次，大多数以前的方法都是为场景几何或材料优化而设计的，并且没有针对优化光源的情况进行广泛的测试。目前可用的可微分光线追踪方法无法提供令人满意的性能，即使在我们经验中相当基本的测试用例上也是如此。在本文中，据我们所知，我们提出了一种新颖的伴随光追踪方法，该方法克服了这些挑战，并以独立于视图（无相机）的方式实现基于梯度的照明设计优化。因此，我们允许用户将照明目标直接绘制到 3D 场景上或使用现有的烘焙照明数据（例如光照图）。使用现代光线追踪硬件，我们实现了交互性能。我们发现在此设置中光追踪优于路径追踪，因为它自然地处理不规则几何形状，从而减少噪音并提高优化收敛性。我们将伴随梯度与最先进的基于图像的可微渲染方法进行比较。我们还证明了我们的梯度数据可以与各种常见的优化算法一起使用，提供良好的收敛行为。 与现实世界场景的定性比较强调了我们方法的实际适用性。