最近的4K深度估计方法,如PatchRefiner(PR),采用基于分块的策略,将高分辨率图像分割成小块。然后,将这些小块级别的深度预测(精细的局部输出)与输入图像的降采样版本的深度预测(粗糙的全局输出)进行融合,以获得单个、一致的高分辨率输出。 尽管取得了成功,但PatchRefiner框架在实际应用中面临着关键的计算效率和可扩展性...
This paper introduces PatchRefiner, an advanced framework for metric single image depth estimation aimed at high-resolution real-domain inputs. While depth estimation is crucial for applications such as autonomous driving, 3D generative modeling, and 3D reconstruction, achieving accurate high-resolution ...
Therefore, we design a patch merging refiner (PMR) downsample module, which utilizes subspace projection to learn a set of restoration basis from the feature space and projects the patch merging feature onto such space, to remove noise and retain the authentic information of feature space while ...