Video Classification/Action Recognition Using AlexNet-Like Two-Stream Spatial and Temporal Networks

In this story, Two-Stream Convolutional Networks for Action Recognition in Videos, (Two-Stream ConvNet), by Visual Geometry Group, University of Oxford, is reviewed. Visual Geometry Group (VGG) is the famous research group. In this paper:

This is a paper in 2014 NIPS with over 5400 citations. (Sik-Ho Tsang @ Medium)


1. Two-Stream CNN: Network Architecture

Two-Stream CNN: Network Architecture

AlexNet-Like Network with Spatial Pyramid Pooling layer in SPPNet for Video Classification

Given a video for testing, DevNet not only provides an event label but also spatial-temporal key evidences.

In this story, DevNet: Deep Event Network for Multimedia Event Detection and Evidence Recounting, (DevNet), by Tsinghua University, Hong Kong University of Science and Technology, University of Technology, Sydney, and Carnegie Mellon University, is reviewed.

An event is a semantic abstraction of video sequences of higher level than a concept and often consists of multiple concepts.

A long unconstrained video may contain a lot of irrelevant information and even the same event label may contain large intra-class variations.

In this paper:

Blur Classification Using Wavelet + Neural Network

Blur Classification Framework

In this story, Blur Classification Using Wavelet Transform and Feed Forward Neural Network, (Tiwari IJMECS’14), by Mody Institute of Technology & Science, is briefly reviewed. In this paper:

This is a paper in 2014 IJMECS. (Sik-Ho Tsang @ Medium)


1. Preprocessing

Feature Extraction Using DCT, Classification Using RF Outperforms Naïve Bayes, MLP, k-NN, SVM

In this story, Comparative Study of Classifiers for Blurred Images, (Gueraichi SAI’20), by Houari Boumediene University of Science and Technology, is reviewed. In this paper:

This is a paper in 2020 SAI. (Sik-Ho Tsang @ Medium)


1. Features Extraction Using DCT

Representation of (8 × 8) DCT bloc Frequency bands

Blur Classification Using Curvelet Transform + Neural Network

Motion Blur of a QR Code

In this story, A Pattern Classification Based Approach for Blur Classification, (Tiwari IJEEI’17), by Mody University of Science & Technology, is reviewed. In this paper:

This is a paper in 2017 IJEEI. (Sik-Ho Tsang @ Medium)


1. Pre-processing

Blur Classification for Hand Gesture Images Using CNN

In this story, A Blur Classification Approach Using Deep Convolution Neural Network, (Tiwari IJISMD’20), by University of Petroleum and Energy Studies, is reviewed. In this paper:

This is a paper in 2020 IJISMD. (Sik-Ho Tsang @ Medium)


1. Blur Models

1.1. Motion Blur

A 2-Conv+4-FC Model to Classify if an Image is Blurry or not

Images described by an expert as blurry (left) and sharp (right).

In this story, Convolutional Neural Network for Blur Images Detection as an Alternative for Laplacian Method,(Szandała SSCI’20), by Wroclaw University of Science and Technology, is briefly reviewed, as I’m studying this problem recently.

The photographers employed for picturing ceremonies such as weddings admit that as many as 40% of the images have insufficient quality to be proposed to a client. One of the key factors that lead to quality degradation is blur.

This is a paper in 2020 SSCI. (Sik-Ho Tsang @ Medium)


Blur Classification Using Ensemble of Simplified-Fast-GoogleNet (SFGA) and Simplified-Fast-AlexNet (SFA)

Sample images in blur datasets

In this story, Blur image identification with ensemble convolution neural networks, (SFA & SFGN), by Beihang University and University of Connecticut, is reviewed.

Blur image type classification is essential to blur image recovery.

In this paper:

This is a paper in 2019 JPR with high impact factor of 4.384. This paper is an extension of SFA in 2017 IST. (Sik-Ho Tsang @ Medium)


Blur Image Classification Using Simplified AlexNet

Samples of Blurred Images

In this story, Blur Image Classification based on Deep Learning, (SFA), is reviewed. In this paper:

This is a paper in 2017 IST. (Sik-Ho Tsang @ Medium)


1. Brief Overview of Image Blur Modelling

Using DSepConv for Video Frame Interpolation, Outperforms DeepFrame

Block diagram of the proposed inter coding scheme with the architecture of interpolation network from DSepConv [10].

In this story, Deep Inter Coding with Interpolated Reference Frame for Hierarchical Coding Structure, (Guo VCIP’20), is briefly reviewed. In this paper:

This is a paper in 2020 VCIP. (Sik-Ho Tsang @ Medium)


1. Generation of Interpolated Reference Frame

1.1. Hierarchical B Coding Structure

Sik-Ho Tsang

PhD, Researcher. I share what I've learnt and done. :) My LinkedIn:, My Paper Reading List:

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