Specifically, SegRefiner takes coarse masks as inputs and refines them using a discrete diffusion process.

To leverage the complementary merits of both worlds, we propose BetterDepth to achieve geometrically correct affine-invariant MDE while capturing fine details.

Ensuring robust 3D object detection and localization is crucial for many applications in robotics and autonomous driving.

If we consider for example the image pictured in Figure 1 on the left, we can easily describe its content by'what' we see - the building, sky and a flag.

We provide more visualization results in Figure 1, Figure 1, Figure 1, and Figure 1. As mentioned in the limitation section of the main text, our method can generate realistic textures in most regions. However, it may restore incorrect small characters as shown in Figure 1, which is highly ill-posed. Compared with the Uformer, it shows consistent improvements in perceptual quality. Learning to see in the dark. We compare the PSNR-oriented methods and our method.