Fetching the paper…
Reading the bibliography…
Recent advances in computer vision-in the form of deep neural networks-have made it possible to query increasing volumes of video data with high accuracy.
The summer vision project
S. A. Papert · 1966
Earlier work this paper cites.
Access path selection in a relational database management system
P. G. Selinger et al · 1979
Earlier work this paper cites.
Image processing on compressed data for large video databases
F. Arman et al · 1993
Earlier work this paper cites.
Audio/video databases: An object-oriented approach
S. Gibbs et al · 1993
Earlier work this paper cites.
Metadata in video databases
R. Jain and A. Hampapur · 1994
Earlier work this paper cites.
Motion tracking with an active camera
D. Murray and A. Basu · 1994
Earlier work this paper cites.
Query by image and video content: The QBIC system
M. Flickner et al · 1995
Earlier work this paper cites.
Chabot: Retrieval from a relational database of images
V. E. Ogle and M. Stonebraker · 1995
Earlier work this paper cites.
Jacob: Just a content-based query system for video databases
M. La Cascia and E. Ardizzone · 1996
Earlier work this paper cites.
Scene change detection techniques for video database systems
H. Jiang et al · 1998
Earlier work this paper cites.
A survey on the automatic indexing of video data
R. Brunelli, O. Mich, and C. M. Modena · 1999
Earlier work this paper cites.
Optimization of queries with user-defined predicates
S. Chaudhuri and K. Shim · 1999
Earlier work this paper cites.
Object recognition from local scale-invariant features
D. G. Lowe · 1999
Earlier work this paper cites.
A survey on content-based retrieval for multimedia databases
A. Yoshitaka and T. Ichikawa · 1999
Earlier work this paper cites.
Efficient and cost-effective techniques for browsing and indexing large video databases
J. Oh and K. A. Hua · 2000
Earlier work this paper cites.
Rapid object detection using a boosted cascade of simple features
P. Viola and M. Jones · 2001
Earlier work this paper cites.
Video query processing in the VDBMS testbed for video database research
W. Aref et al · 2003
Earlier work this paper cites.
TelegraphCQ: Continuous dataflow processing for an uncertain world
S. Chandrasekaran et al · 2003
Earlier work this paper cites.
Gigascope: a stream database for network applications
C. Cranor et al · 2003
Earlier work this paper cites.
A survey of video processing techniques for traffic applications
V. Kastrinaki, M. Zervakis, and K. Kalaitzakis · 2003
Earlier work this paper cites.
Efficient region-based motion segmentation for a video monitoring system
J. B. Kim and H. J. Kim · 2003
Earlier work this paper cites.
Face recognition: A literature survey
W. Zhao et al · 2003
Earlier work this paper cites.
Operator scheduling in data stream systems
B. Babcock et al · 2004
Earlier work this paper cites.
Adaptive ordering of pipelined stream filters
S. Babu et al · 2004
Earlier work this paper cites.
The design of the Borealis stream processing engine
D. J. Abadi et al · 2005
Earlier work this paper cites.
Strg-index: Spatio-temporal region graph indexing for large video databases
J. Lee, J. Oh, and S. Hwang · 2005
Earlier work this paper cites.
Video data mining: Semantic indexing and event detection from the association perspective
X. Zhu et al · 2005
Earlier work this paper cites.
Model compression
C. Bucilua et al · 2006
Earlier work this paper cites.
Wavescope: a signal-oriented data stream management system
L. Girod et al · 2006
Earlier work this paper cites.
Object tracking: A survey
A. Yilmaz et al · 2006
Earlier work this paper cites.
Fast human detection using a cascade of histograms of oriented gradients
Q. Zhu et al · 2006
Earlier work this paper cites.
Self-tuning database systems: a decade of progress
S. Chaudhuri and V. Narasayya · 2007
Earlier work this paper cites.
Database cracking
S. Idreos, M. L. Kersten, S. Manegold, et al · 2007
Earlier work this paper cites.
A survey of image classification methods and techniques for improving classification performance
D. Lu and Q. Weng · 2007
Earlier work this paper cites.
Optimization of continuous queries with shared expensive filters
K. Munagala et al · 2007
Cited alongside, same era.
Object retrieval with large vocabularies and fast spatial matching
J. Philbin et al · 2007
Cited alongside, same era.
License plate recognition from still images and video sequences: A survey
C.-N. E. Anagnostopoulos et al · 2008
Cited alongside, same era.
A unified learning framework for object detection and classification using nested cascades of boosted classifiers
R. Verschae et al · 2008
Cited alongside, same era.
Object detection with discriminatively trained part-based models
P. F. Felzenszwalb et al · 2010
Cited alongside, same era.
Computer vision: algorithms and applications
R. Szeliski · 2010
Cited alongside, same era.
Learning to track for spatio-temporal action localization
P. Weinzaepfel et al · 2015
Later among the works it cites.
Exploiting local features from deep networks for image retrieval
J. Yue-Hei Ng, F. Yang, and L. S. Davis · 2015
Later among the works it cites.
Technical report, 2016
Cisco VNI forecast and methodology, 2015-2020 · 2016
Later among the works it cites.
Beyond correlation filters: Learning continuous convolution operators for visual tracking
M. Danelljan et al · 2016
Later among the works it cites.
Online deformable object tracking based on structure-aware hyper-graph
D. Du et al · 2016
Later among the works it cites.
Spatiotemporal residual networks for video action recognition
C. Feichtenhofer et al · 2016
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Robust object tracking with online multiple instance learning
B. Babenko et al · 2011
Cited alongside, same era.
Video processing techniques for traffic flow monitoring: A survey
B. Tian, Q. Yao, Y. Gu, K. Wang, and Y. Li · 2011
Cited alongside, same era.
Pedestrian detection: An evaluation of the state of the art
P. Dollar et al · 2012
Cited alongside, same era.
The PASCAL Visual Object Classes Challenge 2012 (VOC2012) Results
M. Everingham et al · 2012
Cited alongside, same era.
Towards a unified architecture for in-RDBMS analytics
X. Feng et al · 2012
Cited alongside, same era.
Are we ready for autonomous driving? the kitti vision benchmark suite
A. Geiger, P. Lenz, and R. Urtasun · 2012
Cited alongside, same era.
Deep Learning
I. Goodfellow, Y. Bengio, and A. Courville · 2016
Later among the works it cites.
Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding
S. Han et al · 2016
Later among the works it cites.
EIE: efficient inference engine on compressed deep neural network
S. Han et al · 2016
Later among the works it cites.
Seq-nms for video object detection
W. Han et al · 2016
Later among the works it cites.
Deep residual learning for image recognition
K. He et al · 2016
Later among the works it cites.
Object detection from video tubelets with convolutional neural networks
K. Kang et al · 2016
Later among the works it cites.
T-cnn: Tubelets with convolutional neural networks for object detection from videos
K. Kang et al · 2016
Later among the works it cites.
The visual object tracking vot2016 challenge results
M. Kristan et al · 2016
Later among the works it cites.
Sequential Monte Carlo filter based on multiple strategies for a scene specialization classifier
H. Maâmatou et al · 2016
Later among the works it cites.
Faster R-CNN scene specialization with a sequential Monte-Carlo framework
A. Mhalla et al · 2016
Later among the works it cites.
Modeling and propagating cnns in a tree structure for visual tracking
H. Nam et al · 2016
Later among the works it cites.
High performance video encoding with NVIDIA GPUs
A. Patait and E. Young · 2016
Later among the works it cites.
Xnor-net: Imagenet classification using binary convolutional neural networks
M. Rastegari et al · 2016
Later among the works it cites.
Minerva: Enabling low-power, highly-accurate deep neural network accelerators
B. Reagen et al · 2016
Later among the works it cites.
You only look once: Unified, real-time object detection
J. Redmon et al · 2016
Later among the works it cites.
Yolo9000: Better, faster, stronger
J. Redmon and A. Farhadi · 2016
Later among the works it cites.
Predicting non-small cell lung cancer prognosis by fully automated microscopic pathology image features
K.-H. Yu et al · 2016
Later among the works it cites.
How far are we from solving pedestrian detection?
S. Zhang et al · 2016
Later among the works it cites.
https://fortunelords.com/youtube-statistics/
2017 · 2017
Closest in time.
Macrobase: Prioritizing attention in fast data
P. Bailis et al · 2017
Closest in time.
Prioritizing attention in fast data: Principles and promise
P. Bailis, E. Gan, K. Rong, and S. Suri · 2017
Closest in time.
Dual deep network for visual tracking
Z. Chi et al · 2017
Closest in time.
Dermatologist-level classification of skin cancer with deep neural networks
A. Esteva et al · 2017
Closest in time.
Technical perspective: What led computer vision to deep learning?
J. Malik · 2017
Closest in time.
AI is about to learn more like humans—with a little uncertainty
C. Metz · 2017
Closest in time.
Live video analytics at scale with approximation and delay-tolerance
H. Zhang et al · 2017
Closest in time.
Neural architecture search with reinforcement learning
B. Zoph and Q. V. Le · 2017
Closest in time.