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Computer Vision

LOOC: Localize Overlapping Objects with Count Supervision
Acquiring count annotations generally requires less human effort than point-level and bounding box annotations. Thus, we propose the …
Proposal-based Instance Segmentation with Point Supervision
Instance segmentation methods often require costly per-pixel labels. We propose a method called WISE-Net that only requires point-level …
Embedding Propagation: Smoother Manifold for Few-Shot Classification
Few-shot classification is challenging because the data distribution of the training set can be widely different to the test set as …
HighRes-net: Recursive Fusion for Multi-Frame Super-Resolution of Satellite Imagery
Generative deep learning has sparked a new wave of Super-Resolution (SR) algorithms that enhance single images with impressive …
A realistic fish-habitat dataset to evaluate algorithms for underwater visual analysis
Visual analysis of complex fish habitats is an important step towards sustainable fisheries for human consumption and environmental …
Class-Based Styling: Real-time Localized Style Transfer with Semantic Segmentation
We propose a Class-Based Styling method (CBS) that can map different styles for different object classes in real-time. CBS achieves …
Class-Based Styling: Real-time Localized Style Transfer with Semantic Segmentation
We propose a Class-Based Styling method (CBS) that can map different styles for different object classes in real-time. CBS achieves …
Where are the Masks: Instance Segmentation with Image-level Supervision
A major obstacle in instance segmentation is that existing methods often need many per-pixel labels in order to be effective. These …
Context-Aware Visual Compatibility Prediction
How do we determine whether two or more clothing items are compatible or visually appealing? Part of the answer lies in understanding …
Pix2Shape: Towards Unsupervised Learning of 3D Scenes from Images using a View-based Representation
We infer and generate three-dimensional (3D) scene information from a single input image and without supervision. This problem is …