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Learning Continually from Low-shot Data Stream [article]

Canyu Le, Xihan Wei, Biao Wang, Lei Zhang, Zhonggui Chen
2019 arXiv   pre-print
In this work, we propose a novel approach, MetaCL, which enables neural networks to effectively learn meta knowledge from low-shot data stream without catastrophic forgetting.  ...  To solve these two limits, the deep learning model should not only be able to learn from a few of data, but also incrementally learn new concepts from data stream over time without forgetting the previous  ...  We observe the performance changes when we train model on different sizes of training data. Tab. 6, 7 outline all quantitative results when we set K = 20, 50, 200, 500.  ... 
arXiv:1908.10223v2 fatcat:xzqxm4cu2fhf5pd3dhhqdj4oma

Online Continual Learning for Embedded Devices [article]

Tyler L. Hayes, Christopher Kanan
2022 arXiv   pre-print
data streams.  ...  We then study the efficacy of several online continual learning methods when used with mobile neural networks.  ...  streams, large-scale data streams, video streams, and low-shot video streams).  ... 
arXiv:2203.10681v3 fatcat:ygkrakhtxnbthff7j3aw2qnodq

FLUID: A Unified Evaluation Framework for Flexible Sequential Data [article]

Matthew Wallingford, Aditya Kusupati, Keivan Alizadeh-Vahid, Aaron Walsman, Aniruddha Kembhavi, Ali Farhadi
2021 arXiv   pre-print
The sub-fields of few-shot, continual, transfer, and representation learning have made substantial strides in learning under adverse conditions; each affording distinct advantages through methods and insights  ...  FLUID integrates the objectives of few-shot, continual, transfer, and representation learning while enabling comparison and integration of techniques across these subfields.  ...  Acknowledgements This work is in part supported by NSF IIS 1652052, IIS 17303166, DARPA N66001-19-2-4031, 67102239 and gifts from Allen Institute for Artificial Intelligence.  ... 
arXiv:2007.02519v5 fatcat:fi7zdcqsmzgftdw733f2qh3nbi

Few-Shot Keyword Spotting in Any Language [article]

Mark Mazumder, Colby Banbury, Josh Meyer, Pete Warden, Vijay Janapa Reddi
2021 arXiv   pre-print
We introduce a few-shot transfer learning method for keyword spotting in any language.  ...  We investigate streaming accuracy for our 5-shot models in two contexts: keyword spotting and keyword search.  ...  Few-Shot Streaming Accuracy In practice, KWS models operate on a continuous stream of audio, thus we inspect streaming accuracy in two regimes. (1) We concatenate individual words with an average gap of  ... 
arXiv:2104.01454v3 fatcat:3dai4ybxvvhgtlpdaws5hwtho4

Learning to Cut by Watching Movies [article]

Alejandro Pardo, Fabian Caba Heilbron, Juan León Alcázar, Ali Thabet, Bernard Ghanem
2021 arXiv   pre-print
To do this, we first collected a data source of more than 10K videos, from which we extract more than 255K cuts.  ...  We devise a model that learns to discriminate between real and artificial cuts via contrastive learning. We set up a new task and a set of baselines to benchmark video cut generation.  ...  Learning to Cut Leveraging Edited Video As a reminder, a shot is a continuous take from the same camera, and a cut occurs between a pair of shots (section 1).  ... 
arXiv:2108.04294v3 fatcat:l2k2dc52mbfnzony2pm4fxybhu

Generalized Continual Zero-Shot Learning [article]

Chandan Gautam, Sethupathy Parameswaran, Ashish Mishra, Suresh Sundaram
2021 arXiv   pre-print
Recently, zero-shot learning (ZSL) emerged as an exciting topic and attracted a lot of attention.  ...  ., continual ZSL (CZSL), where classes arrive sequentially in the form of a task and it actively learns from the changing environment by leveraging the past experience.  ...  new knowledge from streaming data while retaining previously learned information.  ... 
arXiv:2011.08508v3 fatcat:spue4cbhgjdfdflkwdhpobromi

Real-time personalized sports video filtering and summarization

Di Zhong, Raj Kumar, Shih-Fu Chang
2001 Proceedings of the ninth ACM international conference on Multimedia - MULTIMEDIA '01  
Our system includes an event detection module, an adaptive encoding module, and a buffer management module for adaptive streaming.  ...  For wireless video applications, we propose and apply a unique notion of content-based adaptive streaming, in which video encoding rate and media modality is dynamically varied according to the event filtering  ...  One simple filtering criterion for baseball is to mark all pitching shots and subsequent shots showing continuing activities as important.  ... 
doi:10.1145/500141.500264 fatcat:ie74qib7jndgtijr753rculdli

Real-time personalized sports video filtering and summarization

Di Zhong, Raj Kumar, Shih-Fu Chang
2001 Proceedings of the ninth ACM international conference on Multimedia - MULTIMEDIA '01  
Our system includes an event detection module, an adaptive encoding module, and a buffer management module for adaptive streaming.  ...  For wireless video applications, we propose and apply a unique notion of content-based adaptive streaming, in which video encoding rate and media modality is dynamically varied according to the event filtering  ...  One simple filtering criterion for baseball is to mark all pitching shots and subsequent shots showing continuing activities as important.  ... 
doi:10.1145/500249.500264 fatcat:5o2p7bsv3rh5bh5poq6g7rw5um

Executive Function: A Contrastive Value Policy for Resampling and Relabeling Perceptions via Hindsight Summarization? [article]

Chris Lengerich, Ben Lengerich
2022 arXiv   pre-print
We develop the few-shot continual learning task from first principles and hypothesize an evolutionary motivation and mechanism of action for executive function as a contrastive value policy which resamples  ...  We show how this model of executive function can be used to implement hypothesis testing as a stream of consciousness and may explain observations of human few-shot learning and neuroanatomy.  ...  The Continual Few-Shot Learning Constraint We also introduce a few-shot learning constraint of only being able to collect a few examples of data from the environment.  ... 
arXiv:2204.12639v1 fatcat:x7oxt3otxzez3prdrrivvutfky

Use of Generalized Pattern Model for Video Annotation

Yang Xiao, Tat-Seng Chua, Lekha Chaisorn, Chin-Hui Lee
2007 Multimedia and Expo, 2007 IEEE International Conference on  
We discretize the shot contents into fixed set of tokens, and transform the high dimensional continuous video streams into tractable token sequences.  ...  At the sequence level, we aim to find patterns of shot sequences around candidate shots with consistent statistical characteristics and dynamics.  ...  As video is a highdimensional, continuous data stream, in the first step, we decompose the video streams into tractable token sequences.  ... 
doi:10.1109/icme.2007.4284776 dblp:conf/icmcs/XiaoCCL07 fatcat:zt6yuzyv7rhg5fidzw5bqtp46a

Evolving Metric Learning for Incremental and Decremental Features [article]

Jiahua Dong, Yang Cong, Gan Sun, Tao Zhang, Xu Tang, Xiaowei Xu
2021 arXiv   pre-print
Online metric learning has been widely exploited for large-scale data classification due to the low computational cost.  ...  It further explores the intrinsic low-rank structure of heterogeneous samples to reduce the computation and memory burden especially for highly-dimensional large-scale data.  ...  , where the streaming data indicate the continuous data flow that the data samples arrive consecutively in a real-time manner.  ... 
arXiv:2006.15334v2 fatcat:pzgw2s7kffgs3deonif3slpj3m

Defining Benchmarks for Continual Few-Shot Learning [article]

Antreas Antoniou, Massimiliano Patacchiola, Mateusz Ochal, Amos Storkey
2020 arXiv   pre-print
Both few-shot and continual learning have seen substantial progress in the last years due to the introduction of proper benchmarks.  ...  Continual few-shot learning has a small computational footprint and is thus an excellent setting for efficient investigation and experimentation.  ...  This work was supported in part by the EP-SRC Centre for Doctoral Training in Data Science, funded by the UK Engineering and Physical Sciences Research Council (Grant No.  ... 
arXiv:2004.11967v1 fatcat:7bi6xeir65hb7lgfdvreotraja

Classification of Tennis Video Types Based on Machine Learning Technology

Xun Gong, Fucheng Wang, Wenqing Wu
2021 Wireless Communications and Mobile Computing  
This article focuses on video tennis based on the selection of the basic frame of each shot and proposes an algorithm for classification of shots based on average grouping.  ...  With the rapid development of online video data, how to find the required information has become an urgent problem to be solved.  ...  Data Availability Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.  ... 
doi:10.1155/2021/2055703 fatcat:nplk6engmra5ffjaqndccpxluq

Broadcast Video Content Segmentation by Supervised Learning [chapter]

Kevin W. Wilson, Ajay Divakaran
2008 Signals and Communication Technology  
Streaming video over the internet is beginning to add to this flow.  ...  A summary meant to best convey the plot of a situation comedy could differ substantially from a summary meant to show the funniest few scenes from the show.  ...  They define a "computational scene" to be a continuous segment of data that exhibits long-term consistency in its underlying low-level features.  ... 
doi:10.1007/978-0-387-76569-3_3 fatcat:cundyywa5rfrpd5gycnth7mtri

Cross-lingual Lifelong Learning [article]

Meryem M'hamdi, Xiang Ren, Jonathan May
2022 arXiv   pre-print
In this paper, we present the Cross-lingual Lifelong Learning (CLL) challenge, where a model is continually fine-tuned to adapt to emerging data from different languages.  ...  The longstanding goal of multi-lingual learning has been to develop a universal cross-lingual model that can withstand the changes in multi-lingual data distributions.  ...  Data Stream Construction.  ... 
arXiv:2205.11152v1 fatcat:r7f6zlikdjhalfoa7vwkb7crlq
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