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Augundo: Scaling up augmentations for monocular depth completion and estimation
Unsupervised depth completion and estimation methods are trained by minimizing
reconstruction error. Block artifacts from resampling, intensity saturation, and occlusions are …
reconstruction error. Block artifacts from resampling, intensity saturation, and occlusions are …
Uncle: Unsupervised continual learning of depth completion
S Gangopadhyay, X Chen, M Chu, P Rim… - arxiv preprint arxiv …, 2024 - arxiv.org
We propose UnCLe, a standardized benchmark for Unsupervised Continual Learning of a
multimodal depth estimation task: Depth completion aims to infer a dense depth map from a …
multimodal depth estimation task: Depth completion aims to infer a dense depth map from a …
A simple yet universal framework for depth completion
Consistent depth estimation across diverse scenes and sensors is a crucial challenge in
computer vision, especially when deploying machine learning models in the real world …
computer vision, especially when deploying machine learning models in the real world …