Single-Image Depth Prediction Makes Feature Matching Easier
Good local features improve the robustness of many 3D re-localization and multi-view reconstruction pipelines. The problem is that viewing angle and distance severely impact the recognizability of a local feature. Attempts to improve appearance invariance by choosing better local feature points or by leveraging outside information, have come with pre-requisites that made some of them impractical. In this paper, we propose a surprisingly effective enhancement to local feature extraction, which improves matching. We show that CNN-based depths inferred from single RGB images are quite helpful, despite their flaws. They allow us to pre-warp images and rectify perspective distortions, to significantly enhance SIFT and BRISK features, enabling more good matches, even when cameras are looking at the same scene but in opposite directions.
Code (1)
Tasks
Depth EstimationDepth PredictionPredictionSimilar Papers 제목 키워드 기반
Single-Image Depth Prediction Makes Feature Matching Easier
Good local features improve the robustness of many 3D re-localization and multi-view reconstruction pipelines. The problem is that viewing angle and distance severely impact the recognizability of a local feature. Attemp…
Depth EstimationDepth PredictionPredictionDepth Map Prediction from a Single Image using a Multi-Scale Deep Network
Predicting depth is an essential component in understanding the 3D geometry of a scene. While for stereo images local correspondence suffices for estimation, finding depth relations from a single image is less straightfo…
3D geometryMonocular Depth EstimationSliceNet: Deep Dense Depth Estimation From a Single Indoor Panorama Using a Slice-Based Representation
We introduce a novel deep neural network to estimate a depth map from a single monocular indoor panorama. The network directly works on the equirectangular projection, exploiting the properties of indoor 360 images. …
Depth EstimationBoundary-induced and scene-aggregated network for monocular depth prediction
Monocular depth prediction is an important task in scene understanding. It aims to predict the dense depth of a single RGB image. With the development of deep learning, the performance of this task has made great improve…
Depth EstimationDepth PredictionScene UnderstandingVA-DepthNet: A Variational Approach to Single Image Depth Prediction
We introduce VA-DepthNet, a simple, effective, and accurate deep neural network approach for the single-image depth prediction (SIDP) problem. The proposed approach advocates using classical first-order variational const…
Depth EstimationDepth PredictionMonocular Depth Estimation