Learning Geo-Temporal Image Features
We propose to implicitly learn to extract geo-temporal image features, which are mid-level features related to when and where an image was captured, by explicitly optimizing for a set of location and time estimation tasks. To train our method, we take advantage of a large image dataset, captured by outdoor webcams and cell phones. The only form of supervision we provide are the known capture time and location of each image. We find that our approach learns features that are related to natural appearance changes in outdoor scenes. Additionally, we demonstrate the application of these geo-temporal features to time and location estimation.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Spatial Focused Bitemporal Interactive Network for Remote Sensing Image Change Detection
Recently, transformers have been widely explored in remote sensing image change detection and achieved remarkable performance. However, most existing transformer-based change detection methods overlook exploring the spat…
Change DetectionDiversityBeyond still images: Temporal features and input variance resilience
Traditionally, vision models have predominantly relied on spatial features extracted from static images, deviating from the continuous stream of spatiotemporal features processed by the brain in natural vision. While num…
Video UnderstandingMulti-Temporal Aerial Image Registration Using Semantic Features
A semantic feature extraction method for multitemporal high resolution aerial image registration is proposed in this paper. These features encode properties or information about temporally invariant objects such as roads…
Image RegistrationSemantic SegmentationTemporal Hallucinating for Action Recognition With Few Still Images
Action recognition in still images has been recently promoted by deep learning. However, the success of these deep models heavily depends on huge amount of training images for various action categories, which may not be …
Action RecognitionAction Recognition In Still ImagesDomain AdaptationTemporal Action LocalizationA Remote Sensing Image Change Detection Method Integrating Layer Exchange and Channel-Spatial Differences
Change detection in remote sensing imagery is a critical technique for Earth observation, primarily focusing on pixel-level segmentation of change regions between bi-temporal images. The essence of pixel-level change det…
Change DetectionEarth Observation