Lens flare occurs when shooting towards strong light sources, significantly degrading the visual quality of images. Due to the difficulty in capturing flare-corrupted and flare-free image pairs in the real world, existing datasets are typically synthesized in 2D by overlaying artificial flare templates onto background images. However, the lack of flare diversity in templates and the neglect of physical principles in the synthesis process hinder models trained on these datasets from generalizing well to real-world scenarios. To address these challenges, we propose a new physics-informed method for flare data generation, which consists of three stages: parameterized template creation, the laws of illumination-aware 2D synthesis, and physical engine-based 3D rendering, which finally gives us a miXed flare dataset that incorporates both 2D and 3D perspectives, namely FlareX. This dataset offers 9,500 2D templates derived from 95 flare patterns and 3,000 flare image pairs rendered from 60 3D scenes. Furthermore, we design a masking approach to obtain real-world flare-free images from their corrupted counterparts to measure the performance of the model on real-world images. Extensive experiments demonstrate the effectiveness of our method and dataset.

Inverse optimal control can be used to characterize behavior in sequential decisionmaking tasks. Most existing work, however, is limited to fully observable or linear systems, or requires the action signals to be known. Here, we introduce a probabilistic approach to inverse optimal control for partially observable stochastic non-linear systems with unobserved action signals, which unifies previous approaches to inverse optimal control with maximum causal entropy formulations. Using an explicit model of the noise characteristics of the sensory and motor systems of the agent in conjunction with local linearization techniques, we derive an approximate likelihood function for the model parameters, which can be computed within a single forward pass.

In this supplementary material, we present additional details of the proposed Flare7K dataset and experimental settings and show more results. Figure 1: Illustration of a simplified lens system. In the lens and aperture plane, the light passes through the dirty aperture and lens system, leaving a scattering flare on the image plane. In this section, we use a simplified Fourier optics model to illustrate how different kinds of scattering flares occur. A basic lens system can be viewed as a combination of one convex lens, one aperture, and an image plane as shown in Figure 1. We set the optical center as the origin of a coordinate system. Then, the light source's position is (x0,y0, z0). It is a combination of aperture function eAλ(x,y) and a lens function eTL(x,y). Supposing the focus of the lens is f and the lens is ideal. After adjusting the origin of x1 and x2, Equation (11) can be viewed as a standard Fourier transformation. Thus, the point spread function (PSF) which is the square of the amplitude of the image plane's optical field can be written as: PSFλ = |F{eAλ(x,y)}|2. Since stains with depth may bring phase shift for the aperture function, the PSFλ may vary with the wavelength λof the light source.

Artificial lights commonly leave strong lens flare artifacts on images captured at night. Nighttime flare not only affects the visual quality but also degrades the performance of vision algorithms. Existing flare removal methods mainly focus on removing daytime flares and fail in nighttime. Nighttime flare removal is challenging because of the unique luminance and spectrum of artificial lights and the diverse patterns and image degradation of the flares captured at night. The scarcity of nighttime flare removal datasets limits the research on this crucial task.

To help better understand how shadow provides cues for inferring shape of the invisible surface, in Fig. S1, we visualize the rendered images of three different objects, which have the same front view b can ut with see that different although shapes these in three the back objects (generated have the by sam cutting e shapes the and READING appearances mesh in with the front a plane).

Under Display Camera (UDC) is a novel imaging system that mounts a digital camera lens beneath a display panel with the panel covering the camera.

Albeit it is crucial for autonomous driving and night vision, this problem has not been yet focused on as much as other object detection (OD).

Inverse optimal control can be used to characterize behavior in sequential decision-making tasks.

Wu et al. use a feathered saturated mask to replace the light source.