Home /
Research
Showing 67 - 72 / 897
How Can I Explain This to You? An Empirical Study of Deep Neural Network Explanation Methods
JeyaVikranthJeyakumar, JosephNoor, Yu-HsiCheng....
Published date-12/01/2020
SentimentAnalysis
Explaining the inner workings of deep neural network models have received considerable attention in recent years. Researchers have attempted to provide human parseable explanations justifying why a model performed a …
The Dilemma of TriHard Loss and an Element-Weighted TriHard Loss for Person Re-Identification
YihaoLv, YouzhiGu, LiuXinggao....
Published date-12/01/2020
PersonRe-Identification
Triplet loss with batch hard mining (TriHard loss) is an important variation of triplet loss inspired by the idea that hard triplets improve the performance of metric leaning networks. However, …
Learning efficient task-dependent representations with synaptic plasticity
ColinBredenberg, EeroSimoncelli, CristinaSavin....
Published date-12/01/2020
Neural populations encode the sensory world imperfectly: their capacity is limited by the number of neurons, availability of metabolic and other biophysical resources, and intrinsic noise. The brain is presumably …
SRG-Net: Unsupervised Segmentation for Terracotta Warrior Point Cloud with 3D Pointwise CNN methods
YaoHu, GuohuaGeng, KangLi....
Published date-12/01/2020
Clustering
In this paper, we present a seed-region-growing CNN(SRG-Net) for unsupervised part segmentation with 3D point clouds of terracotta warriors. Previous neural network researches in 3D are mainly about supervised classification, …
Unsupervised Anomaly Detection From Semantic Similarity Scores
NimaRafiee, RahilGholamipoor, MarkusKollmann....
Published date-12/01/2020
AnomalyDetection, Out-of-DistributionDetection, SemanticSimilarity, SemanticTextualSimilarity, UnsupervisedAnomalyDetection
In this paper, we present SemSAD, a simple and generic framework for detecting examples that lie out-of-distribution (OOD) for a given training set. The approach is based on learning a …
Make One-Shot Video Object Segmentation Efficient Again
TimMeinhardt, LauraLeal-Taixé....
Published date-12/01/2020
ObjectDetection, SemanticSegmentation, VideoObjectSegmentation, VideoSemanticSegmentation, Youtube-VOS
Video object segmentation (VOS) describes the task of segmenting a set of objects in each frame of a video. In the semi-supervised setting, the first mask of each object is …