Learning segment similarity and alignment in large-scale content based video retrieval
C Jiang, K Huang, S He, X Yang, W Zhang… - Proceedings of the 29th …, 2021 - dl.acm.org
With the explosive growth of web videos in recent years, large-scale Content-Based Video
Retrieval (CBVR) becomes increasingly essential in video filtering, recommendation, and …
Retrieval (CBVR) becomes increasingly essential in video filtering, recommendation, and …
Boundary-aware backward-compatible representation via adversarial learning in image retrieval
Image retrieval plays an important role in the Internet world. Usually, the core parts of
mainstream visual retrieval systems include an online service of the embedding model and …
mainstream visual retrieval systems include an online service of the embedding model and …
Discrimination-aware mechanism for fine-grained representation learning
Recently, with the emergence of retrieval requirements for certain individual in the same
superclass, eg, birds, persons, cars, fine-grained recognition task has attracted a significant …
superclass, eg, birds, persons, cars, fine-grained recognition task has attracted a significant …
Rethinking collaborative metric learning: Toward an efficient alternative without negative sampling
The recently proposed Collaborative Metric Learning (CML) paradigm has aroused wide
interest in the area of recommendation systems (RS) owing to its simplicity and …
interest in the area of recommendation systems (RS) owing to its simplicity and …
Spatio-Temporal Variability Analysis of Vegetation Dynamics in China from 2000 to 2022 Based on Leaf Area Index: A Multi-Temporal Image Classification …
Leaf Area Index (LAI) is one of the most important biophysical parameters of vegetation, and
its dynamic changes can be used as a reflective indicator and differentiation basis of …
its dynamic changes can be used as a reflective indicator and differentiation basis of …
Efficient malware analysis using metric embeddings
Real-world malware analysis consists of a complex pipeline of classifiers and data analysis—
from detection to classification of capabilities to retrieval of unique training samples from …
from detection to classification of capabilities to retrieval of unique training samples from …
HBReiD: Harder batch for re-identification
Triplet loss is a widely adopted loss function in ReID task which pulls the hardest positive
pairs close and pushes the hardest negative pairs far away. However, the selected samples …
pairs close and pushes the hardest negative pairs far away. However, the selected samples …
Towards pointsets representation learning via self-supervised learning and set augmentation
P Arsomngern, C Long… - … on Pattern Analysis …, 2021 - ieeexplore.ieee.org
Deep metric learning is a supervised learning paradigm to construct a meaningful vector
space to represent complex objects. A successful application of deep metric learning to …
space to represent complex objects. A successful application of deep metric learning to …
[PDF][PDF] AntVoice Neural Speaker Embedding System for FFSVC 2020.
This paper presents a comprehensive description of the AntVoice system for the first two
tracks of far-field speaker verification from single microphone array in FFSVC 2020 [1]. The …
tracks of far-field speaker verification from single microphone array in FFSVC 2020 [1]. The …
Towards Interpretable Feature Representation for Domain Adaptation Problem
Deep convolutional neural networks (CNNs) have witnessed a great progress in visual
recognition over the past years. However, deep CNN models are still suffering from the …
recognition over the past years. However, deep CNN models are still suffering from the …