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Found 14 papers, 8 papers with code
Answering Visual-Relational Queries in Web-Extracted Knowledge Graphs
A visual-relational knowledge graph (KG) is a multi-relational graph whose entities are associated with images.
Generalized Presentation Attack Detection: a face anti-spoofing evaluation proposal
Over the past few years, Presentation Attack Detection (PAD) has become a fundamental part of facial recognition systems.
Deep Anomaly Detection for Generalized Face Anti-Spoofing
Face recognition has achieved unprecedented results, surpassing human capabilities in certain scenarios.
Learning to Exploit the Prior Network Knowledge for Weakly-Supervised Semantic Segmentation
Training a Convolutional Neural Network (CNN) for semantic segmentation typically requires to collect a large amount of accurate pixel-level annotations, a hard and expensive task.
Unsupervised learning from videos using temporal coherency deep networks
We here propose two Siamese architectures for Convolutional Neural Networks, and their corresponding novel loss functions, to learn from unlabeled videos, which jointly exploit the local temporal coherence between contiguous frames, and a global discriminative margin used to separate representations of different videos.
Visual Semantic Navigation with Real Robots
Visual Semantic Navigation (VSN) is the ability of a robot to learn visual semantic information for navigating in unseen environments.
The Instantaneous Accuracy: a Novel Metric for the Problem of Online Human Behaviour Recognition in Untrimmed Videos
The problem of Online Human Behaviour Recognition in untrimmed videos, aka Online Action Detection (OAD), needs to be revisited.
Rethinking Online Action Detection in Untrimmed Videos: A Novel Online Evaluation Protocol
Our results confirm the problems of the previous evaluation protocols, and suggest that an IA-based protocol is more adequate to the online scenario.
Learning Short-Cut Connections for Object Counting
Standard short-cut connections are connections between layers in deep neural networks which skip at least one intermediate layer.
The challenge of simultaneous object detection and pose estimation: a comparative study
Detecting objects and estimating their pose remains as one of the major challenges of the computer vision research community.
In pixels we trust: From Pixel Labeling to Object Localization and Scene Categorization
While there has been significant progress in solving the problems of image pixel labeling, object detection and scene classification, existing approaches normally address them separately.
ISA$^2$: Intelligent Speed Adaptation from Appearance
Technically, the goal of an ISA$^2$ model is to predict for a given image of a driving scenario the proper speed of the vehicle.
Embarrassingly Simple Model for Early Action Proposal
Early action proposal consists in generating high quality candidate temporal segments that are likely to contain an action in a video stream, as soon as they happen.
Realistic Continual Learning Approach using Pre-trained Models
Continual learning (CL) is crucial for evaluating adaptability in learning solutions to retain knowledge.
