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Found 8 papers, 0 papers with code
Hierarchical Lovasz Embeddings for Proposal-Free Panoptic Segmentation
We use a hierarchical Lovasz hinge loss to learn a low-dimensional embedding space structured into a unified semantic and instance hierarchy without requiring separate network branches or object proposals.
Hierarchical Lovász Embeddings for Proposal-free Panoptic Segmentation
We use a hierarchical Lov\'asz hinge loss to learn a low-dimensional embedding space structured into a unified semantic and instance hierarchy without requiring separate network branches or object proposals.
Multimodal Explanations by Predicting Counterfactuality in Videos
This study addresses generating counterfactual explanations with multimodal information.
Learning to Explain with Complemental Examples
This paper addresses the generation of explanations with visual examples.
Viewpoint-aware Video Summarization
To satisfy these requirements (A)-(C) simultaneously, we proposed a novel video summarization method from multiple groups of videos.
Multi-Label Ranking From Positive and Unlabeled Data
Such a setting has been studied as a positive and unlabeled (PU) classification problem in a binary setting.
Recognizing Activities of Daily Living with a Wrist-mounted Camera
We present a novel dataset and a novel algorithm for recognizing activities of daily living (ADL) from a first-person wearable camera.
MILJS : Brand New JavaScript Libraries for Matrix Calculation and Machine Learning
Our core library offering a matrix calculation is called Sushi, which exhibits far better performance than any other leading machine learning libraries written in JavaScript.
