Computer Vision
The ALFRED environment features embodied instruction following tasks in simulated home environments. However, end-to-end deep learning …
Transfer learning from large-scale pre-trained models has become essential for many computer vision tasks. Recent studies have shown …
We introduce Neural Point Light Fields that represent scenes implicitly with a light field living on a sparse point cloud. Combining …
Like humans devoid of imagination, current machine learning systems lack the ability to adapt to new, unexpected situations by …
Rationale and objectives: Hard data labels for automated algorithm training are binary and cannot incorporate uncertainty between …
Recent progress in self-supervision shows that pre-training large neural networks on vast amounts of unsupervised data can lead to …
Labeling data is often expensive and time-consuming, especially for tasks such as object detection and instance segmentation, which …
Health professionals extensively use Two-Dimensional (2D) Ultrasound (US) videos and images to visualize and measure internal organs …
Explainability for machine learning models has gained considerable attention within the research community given the importance of …
Remote sensing and automatic earth monitoring are key to solve global-scale challenges such as disaster prevention, land use …