A 3D digital scene contains many components: lights, materials and
geometries, interacting to reach the desired appearance. Staging such a scene
is time-consuming and requires both artistic and technical skills. In this
work, we propose PSDR-Room, a system allowing to optimize lighting as well as
the pose and materials of individual objects to match a target image of a room
scene, with minimal user input. To this end, we leverage a recent path-space
differentiable rendering approach that provides unbiased gradients of the
rendering with respect to geometry, lighting, and procedural materials,
allowing us to optimize all of these components using gradient descent to
visually match the input photo appearance. We use recent single-image scene
understanding methods to initialize the optimization and search for appropriate
3D models and materials. We evaluate our method on real photographs of indoor
scenes and demonstrate the editability of the resulting scene components.

利用 PSDR-Room 系统，通过梯度下降来优化光照、物体姿态和材质，以使其与目标室内场景图像视觉上匹配，实现对室内场景中各组件的可编辑性。

PSDR-Room：利用可微渲染的单张照片生成场景

PSDR-Room: Single Photo to Scene using Differentiable Rendering

Inverse path tracing has recently been applied to joint material and lighting
estimation, given geometry and multi-view HDR observations of an indoor scene.
However, it has two major limitations: path tracing is expensive to compute,
and ambiguities exist between reflection and emission. We propose a novel
Factorized Inverse Path Tracing (FIPT) method which utilizes a factored light
transport formulation and finds emitters driven by rendering errors. Our
algorithm enables accurate material and lighting optimization faster than
previous work, and is more effective at resolving ambiguities. The exhaustive
experiments on synthetic scenes show that our method (1) outperforms
state-of-the-art indoor inverse rendering and relighting methods particularly
in the presence of complex illumination effects; (2) speeds up inverse path
tracing optimization to less than an hour. We further demonstrate robustness to
noisy inputs through material and lighting estimates that allow plausible
relighting in a real scene. The source code is available at:
this https URL

通过提出新的 Factorized Inverse Path Tracing 方法，利用 light transport formulation，追踪错误驱动的 emitters，实现了比之前工作更快、更准确地优化材料和照明，特别是在复杂光照效果存在的情况下，成功解决了反射和发射之间的歧义。