Video Applications

Papers

Published: 09 Oct 2015

Unsupervised Learning

Restricted Boltzmann Machine (RBM)

Published: 09 Oct 2015

Transfer Learning

Papers

Published: 09 Oct 2015

Training Deep Neural Networks

Tutorials

Published: 09 Oct 2015

Tracking

Learning A Deep Compact Image Representation for Visual Tracking

Hierarchical Convolutional Features for Visual Tracking

Robust Visual Tracking via Convolutional Networks

Transferring Rich Feature Hierarchies for Robust Visual Tracking

Learning Multi-Domain Convolutional Neural Networks for Visual Tracking

RATM: Recurrent Attentive Tracking Model

Understanding and Diagnosing Visual Tracking Systems

Recurrently Target-Attending Tracking

Visual Tracking with Fully Convolutional Networks

Deep Tracking: Seeing Beyond Seeing Using Recurrent Neural Networks

Learning to Track at 100 FPS with Deep Regression Networks

Learning by tracking: Siamese CNN for robust target association

Fully-Convolutional Siamese Networks for Object Tracking

Hedged Deep Tracking

Spatially Supervised Recurrent Convolutional Neural Networks for Visual Object Tracking

Visual Tracking via Shallow and Deep Collaborative Model

Beyond Correlation Filters: Learning Continuous Convolution Operators for Visual Tracking

Unsupervised Learning from Continuous Video in a Scalable Predictive Recurrent Network

Modeling and Propagating CNNs in a Tree Structure for Visual Tracking

Robust Scale Adaptive Kernel Correlation Filter Tracker With Hierarchical Convolutional Features

Deep Tracking on the Move: Learning to Track the World from a Moving Vehicle using Recurrent Neural Networks

OTB Results: visual tracker benchmark results

Convolutional Regression for Visual Tracking

Semantic tracking: Single-target tracking with inter-supervised convolutional networks

SANet: Structure-Aware Network for Visual Tracking

ECO: Efficient Convolution Operators for Tracking

Dual Deep Network for Visual Tracking

Deep Motion Features for Visual Tracking

Globally Optimal Object Tracking with Fully Convolutional Networks

Robust and Real-time Deep Tracking Via Multi-Scale Domain Adaptation

Tracking The Untrackable: Learning To Track Multiple Cues with Long-Term Dependencies

Large Margin Object Tracking with Circulant Feature Maps

DCFNet: Discriminant Correlation Filters Network for Visual Tracking

End-to-end representation learning for Correlation Filter based tracking

Context-Aware Correlation Filter Tracking

Robust Multi-view Pedestrian Tracking Using Neural Networks

https://arxiv.org/abs/1704.06370

Re3 : Real-Time Recurrent Regression Networks for Object Tracking

Robust Tracking Using Region Proposal Networks

https://arxiv.org/abs/1705.10447

Hierarchical Attentive Recurrent Tracking

Siamese Learning Visual Tracking: A Survey

https://arxiv.org/abs/1707.00569

Robust Visual Tracking via Hierarchical Convolutional Features

CREST: Convolutional Residual Learning for Visual Tracking

Learning Policies for Adaptive Tracking with Deep Feature Cascades

Recurrent Filter Learning for Visual Tracking

Correlation Filters with Weighted Convolution Responses

Semantic Texture for Robust Dense Tracking

https://arxiv.org/abs/1708.08844

Learning Multi-frame Visual Representation for Joint Detection and Tracking of Small Objects

https://arxiv.org/abs/1709.04666

Tracking Persons-of-Interest via Unsupervised Representation Adaptation

End-to-end Flow Correlation Tracking with Spatial-temporal Attention

https://arxiv.org/abs/1711.01124

UCT: Learning Unified Convolutional Networks for Real-time Visual Tracking

Pixel-wise object tracking

https://arxiv.org/abs/1711.07377

MAVOT: Memory-Augmented Video Object Tracking

https://arxiv.org/abs/1711.09414

Learning Hierarchical Features for Visual Object Tracking with Recursive Neural Networks

https://arxiv.org/abs/1801.02021

Parallel Tracking and Verifying

https://arxiv.org/abs/1801.10496

Saliency-Enhanced Robust Visual Tracking

https://arxiv.org/abs/1802.02783

A Twofold Siamese Network for Real-Time Object Tracking

Learning Dynamic Memory Networks for Object Tracking

https://arxiv.org/abs/1803.07268

Context-aware Deep Feature Compression for High-speed Visual Tracking

VITAL: VIsual Tracking via Adversarial Learning

Unveiling the Power of Deep Tracking

https://arxiv.org/abs/1804.06833

A Novel Low-cost FPGA-based Real-time Object Tracking System

MV-YOLO: Motion Vector-aided Tracking by Semantic Object Detection

https://arxiv.org/abs/1805.00107

Information-Maximizing Sampling to Promote Tracking-by-Detection

https://arxiv.org/abs/1806.02523

Instance Segmentation and Tracking with Cosine Embeddings and Recurrent Hourglass Networks

Stochastic Channel Decorrelation Network and Its Application to Visual Tracking

https://arxiv.org/abs/1807.01103

Fast Dynamic Convolutional Neural Networks for Visual Tracking

https://arxiv.org/abs/1807.03132

DeepTAM: Deep Tracking and Mapping

https://arxiv.org/abs/1808.01900

Distractor-aware Siamese Networks for Visual Object Tracking

Multi-Branch Siamese Networks with Online Selection for Object Tracking

Real-Time MDNet

Towards a Better Match in Siamese Network Based Visual Object Tracker

DensSiam: End-to-End Densely-Siamese Network with Self-Attention Model for Object Tracking

Deformable Object Tracking with Gated Fusion

https://arxiv.org/abs/1809.10417

Deep Attentive Tracking via Reciprocative Learning

Online Visual Robot Tracking and Identification using Deep LSTM Networks

  • intro: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, Canada, 2017. IROS RoboCup Best Paper Award
  • arxiv: https://arxiv.org/abs/1810.04941

Detect or Track: Towards Cost-Effective Video Object Detection/Tracking

Deep Siamese Networks with Bayesian non-Parametrics for Video Object Tracking

https://arxiv.org/abs/1811.07386

Fast Online Object Tracking and Segmentation: A Unifying Approach

Siamese Cascaded Region Proposal Networks for Real-Time Visual Tracking

Handcrafted and Deep Trackers: A Review of Recent Object Tracking Approaches

https://arxiv.org/abs/1812.07368

SiamRPN++: Evolution of Siamese Visual Tracking with Very Deep Networks

https://arxiv.org/abs/1812.11703

Deeper and Wider Siamese Networks for Real-Time Visual Tracking

https://arxiv.org/abs/1901.01660

SiamVGG: Visual Tracking using Deeper Siamese Networks

https://arxiv.org/abs/1902.02804

TrackNet: Simultaneous Object Detection and Tracking and Its Application in Traffic Video Analysis

https://arxiv.org/abs/1902.01466

Target-Aware Deep Tracking

  • intro: CVPR 2019
  • intro: 1Harbin Institute of Technology & Shanghai Jiao Tong University & Tencent AI Lab & University of California & Google Cloud AI
  • arxiv: https://arxiv.org/abs/1904.01772

Unsupervised Deep Tracking

Generic Multiview Visual Tracking

https://arxiv.org/abs/1904.02553

SPM-Tracker: Series-Parallel Matching for Real-Time Visual Object Tracking

A Strong Feature Representation for Siamese Network Tracker

https://arxiv.org/abs/1907.07880

Visual Tracking via Dynamic Memory Networks

Multi-Adapter RGBT Tracking

Teacher-Students Knowledge Distillation for Siamese Trackers

https://arxiv.org/abs/1907.10586

Tell Me What to Track

Face Tracking

Mobile Face Tracking: A Survey and Benchmark

https://arxiv.org/abs/1805.09749

Multi-Object Tracking (MOT)

Virtual Worlds as Proxy for Multi-Object Tracking Analysis

Multi-Class Multi-Object Tracking using Changing Point Detection

POI: Multiple Object Tracking with High Performance Detection and Appearance Feature

Simple Online and Realtime Tracking with a Deep Association Metric

Multiple Object Tracking: A Literature Review

Deep Network Flow for Multi-Object Tracking

Online Multi-Object Tracking Using CNN-based Single Object Tracker with Spatial-Temporal Attention Mechanism

https://arxiv.org/abs/1708.02843

Recurrent Autoregressive Networks for Online Multi-Object Tracking

https://arxiv.org/abs/1711.02741

SOT for MOT

Multi-Target, Multi-Camera Tracking by Hierarchical Clustering: Recent Progress on DukeMTMC Project

https://arxiv.org/abs/1712.09531

Multiple Target Tracking by Learning Feature Representation and Distance Metric Jointly

https://arxiv.org/abs/1802.03252

Tracking Noisy Targets: A Review of Recent Object Tracking Approaches

https://arxiv.org/abs/1802.03098

Machine Learning Methods for Solving Assignment Problems in Multi-Target Tracking

Learning to Detect and Track Visible and Occluded Body Joints in a Virtual World

Features for Multi-Target Multi-Camera Tracking and Re-Identification

High Performance Visual Tracking with Siamese Region Proposal Network

Trajectory Factory: Tracklet Cleaving and Re-connection by Deep Siamese Bi-GRU for Multiple Object Tracking

Automatic Adaptation of Person Association for Multiview Tracking in Group Activities

Improving Online Multiple Object tracking with Deep Metric Learning

https://arxiv.org/abs/1806.07592

Tracklet Association Tracker: An End-to-End Learning-based Association Approach for Multi-Object Tracking

Multiple Object Tracking in Urban Traffic Scenes with a Multiclass Object Detector

Tracking by Animation: Unsupervised Learning of Multi-Object Attentive Trackers

https://arxiv.org/abs/1809.03137

Deep Affinity Network for Multiple Object Tracking

Exploit the Connectivity: Multi-Object Tracking with TrackletNet

https://arxiv.org/abs/1811.07258

Multi-Object Tracking with Multiple Cues and Switcher-Aware Classification

MOTS: Multi-Object Tracking and Segmentation

Online Multi-Object Tracking with Instance-Aware Tracker and Dynamic Model Refreshment

https://arxiv.org/abs/1902.08231

Tracking without bells and whistles

Spatial-Temporal Relation Networks for Multi-Object Tracking

Fooling Detection Alone is Not Enough: First Adversarial Attack against Multiple Object Tracking

State-aware Re-identification Feature for Multi-target Multi-camera Tracking

DeepMOT: A Differentiable Framework for Training Multiple Object Trackers

Graph Neural Based End-to-end Data Association Framework for Online Multiple-Object Tracking

End-to-End Learning Deep CRF models for Multi-Object Tracking

https://arxiv.org/abs/1907.12176

End-to-end Recurrent Multi-Object Tracking and Trajectory Prediction with Relational Reasoning

Robust Multi-Modality Multi-Object Tracking

Multiple People Tracking

Multi-Person Tracking by Multicut and Deep Matching

Joint Flow: Temporal Flow Fields for Multi Person Tracking

Multiple People Tracking by Lifted Multicut and Person Re-identification

Tracking by Prediction: A Deep Generative Model for Mutli-Person localisation and Tracking

Real-time Multiple People Tracking with Deeply Learned Candidate Selection and Person Re-Identification

Deep Person Re-identification for Probabilistic Data Association in Multiple Pedestrian Tracking

https://arxiv.org/abs/1810.08565

Multiple People Tracking Using Hierarchical Deep Tracklet Re-identification

https://arxiv.org/abs/1811.04091

Multi-person Articulated Tracking with Spatial and Temporal Embeddings

Instance-Aware Representation Learning and Association for Online Multi-Person Tracking

  • intro: Pattern Recognition
  • intro: Sun Yat-sen University & Guangdong University of Foreign Studies & Carnegie Mellon University & University of California & Guilin University of Electronic Technology & WINNER Technology
  • arxiv: https://arxiv.org/abs/1905.12409

Online Multiple Pedestrian Tracking using Deep Temporal Appearance Matching Association

Tracking with Reinforcement Learning

Deep Reinforcement Learning for Visual Object Tracking in Videos

Visual Tracking by Reinforced Decision Making

End-to-end Active Object Tracking via Reinforcement Learning

https://arxiv.org/abs/1705.10561

Action-Decision Networks for Visual Tracking with Deep Reinforcement Learning

Tracking as Online Decision-Making: Learning a Policy from Streaming Videos with Reinforcement Learning

https://arxiv.org/abs/1707.04991

Detect to Track and Track to Detect

Projects

Tensorflow_Object_Tracking_Video

Resources

Multi-Object-Tracking-Paper-List

Published: 09 Oct 2015

Super-Resolution

Papers

Published: 09 Oct 2015

Style Transfer

Neural Art

A Neural Algorithm of Artistic Style

Image Style Transfer Using Convolutional Neural Networks

Artificial Startup Style: Neural art about startup fashion

From Pixels to Paragraphs: How artistic experiments with deep learning guard us from hype

Experiments with style transfer

Style Transfer for Headshot Portraits (SIGGRAPH 2014)

Teaching recurrent Neural Networks about Monet

Content Aware Neural Style Transfer

Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesis

Stylenet: Neural Network with Style Synthesis

Ostagram

  • intro: This program presents web-service for algorithm combining the content of one image with the style of another image using convolutional neural networks
  • github: https://github.com/SergeyMorugin/ostagram

Exploring the Neural Algorithm of Artistic Style

Perceptual Losses for Real-Time Style Transfer and Super-Resolution

Image transformation networks with fancy loss functions

Improving the Neural Algorithm of Artistic Style

CubistMirror: an openframeworks app which repeatedly applies real-time style transfer on a webcam

Transfer Style But Not Color

neural-art-mini: Lightweight version of mxnet neural art implementation

Preserving Color in Neural Artistic Style Transfer

End to End Neural Art with Generative Models

Neural Style Explained

Texture Networks: Feed-forward Synthesis of Textures and Stylized Images

Learning Typographic Style

Instance Normalization: The Missing Ingredient for Fast Stylization

Painting style transfer for head portraits using convolutional neural networks

Style-Transfer via Texture-Synthesis

neural-style-tf: TensorFlow implementation of Neural Style

Deep Convolutional Networks as Models of Generalization and Blending Within Visual Creativity

  • intro: In Proceedings of the 7th International Conference on Computational Creativity. Palo Alto: Association for the Advancement of Artificial Intelligence (AAAI) Press (2016)
  • arxiv: https://arxiv.org/abs/1610.02478

A Learned Representation For Artistic Style

How to Fake It As an Artist with Docker, AWS and Deep Learning

Multistyle Pastiche Generator

Fast Style Transfer in TensorFlow

Neural Style Transfer For Chinese Fonts

Neural Style Representations and the Large-Scale Classification of Artistic Style

Controlling Perceptual Factors in Neural Style Transfer

Awesome Typography: Statistics-Based Text Effects Transfer

Fast Patch-based Style Transfer of Arbitrary Style

Demystifying Neural Style Transfer

Son of Zorn’s Lemma: Targeted Style Transfer Using Instance-aware Semantic Segmentation

Bringing Impressionism to Life with Neural Style Transfer in Come Swim

  • intro: a case study of how Neural Style Transfer can be used in a movie production context
  • keywords: Kristen Stewart !
  • arxiv: https://arxiv.org/abs/1701.04928

Pytorch tutorials for Neural Style transfert

Stable and Controllable Neural Texture Synthesis and Style Transfer Using Histogram Losses

Arbitrary Style Transfer In Real-Time With Adaptive Instance Normalization

Picking an optimizer for Style Transfer

Multi-style Generative Network for Real-time Transfer

https://arxiv.org/abs/1703.06953

Deep Photo Style Transfer

Lightweight Neural Style on Pytorch

https://github.com/lizeng614/SqueezeNet-Neural-Style-Pytorch

StyleBank: An Explicit Representation for Neural Image Style Transfer

How to Make an Image More Memorable? A Deep Style Transfer Approach

Visual Attribute Transfer through Deep Image Analogy

Characterizing and Improving Stability in Neural Style Transfer

https://arxiv.org/abs/1705.02092

Towards Metamerism via Foveated Style Transfer

https://arxiv.org/abs/1705.10041

Style Transfer for Sketches with Enhanced Residual U-net and Auxiliary Classifier GAN

https://arxiv.org/abs/1706.03319

Meta Networks for Neural Style Transfer

Neural Color Transfer between Images

Improved Style Transfer by Respecting Inter-layer Correlations

https://arxiv.org/abs/1801.01933

Face Destylization

https://arxiv.org/abs/1802.01237

Unsupervised Typography Transfer

https://arxiv.org/abs/1802.02595

Stereoscopic Neural Style Transfer

Arbitrary Style Transfer with Deep Feature Reshuffle

https://arxiv.org/abs/1805.04103

Avatar-Net: Multi-scale Zero-shot Style Transfer by Feature Decoration

Beyond Textures: Learning from Multi-domain Artistic Images for Arbitrary Style Transfer

https://arxiv.org/abs/1805.09987

A Comprehensive Comparison between Neural Style Transfer and Universal Style Transfer

https://arxiv.org/abs/1806.00868

Unbiased Image Style Transfer

https://arxiv.org/abs/1807.01424

Uncorrelated Feature Encoding for Faster Image Style Transfer

https://arxiv.org/abs/1807.01493

Adjustable Real-time Style Transfer

Automated Deep Photo Style Transfer

Attention-aware Multi-stroke Style Transfer

https://arxiv.org/abs/1901.05127

StyleNAS: An Empirical Study of Neural Architecture Search to Uncover Surprisingly Fast End-to-End Universal Style Transfer Networks

https://arxiv.org/abs/1906.02470

StyleNAS: An Empirical Study of Neural Architecture Search to Uncover Surprisingly Fast End-to-End Universal Style Transfer Networks

https://arxiv.org/abs/1906.02470

Neural Art On Audio

MSc AI Project on generative deep networks and neural style transfer for audio

Neural Song Style

Time Domain Neural Audio Style Transfer

Learning Linear Transformations for Fast Arbitrary Style Transfer

https://arxiv.org/abs/1808.04537

Neural Art On Video

neural-style-video

Instructions for making a Neural-Style movie

Artistic style transfer for videos

Artistic style transfer for videos and spherical images

https://arxiv.org/abs/1708.04538

How Deep Learning Can Paint Videos in the Style of Art’s Great Masters

DeepMovie: Using Optical Flow and Deep Neural Networks to Stylize Movies

Coherent Online Video Style Transfer

https://arxiv.org/abs/1703.09211

Laplacian-Steered Neural Style Transfer

Real-Time Neural Style Transfer for Videos

Multi-Content GAN for Few-Shot Font Style Transfer

https://arxiv.org/abs/1712.00516

Deep Painterly Harmonization

ReCoNet: Real-time Coherent Video Style Transfer Network

Fully-Featured Attribute Transfer

https://arxiv.org/abs/1902.06258

Neural Doodle

Semantic Style Transfer and Turning Two-Bit Doodles into Fine Artworks

Neural Doodle

Faster neural doodle

Feed-forward neural doodle

neural image analogies: Generate image analogies using neural matching and blending

Neural doodle with Keras

https://github.com/fchollet/keras/blob/master/examples/neural_doodle.py

Deep Dreams

deepdream

cnn-vis: Use CNNs to generate images

bat-country: A lightweight, extendible, easy to use Python package for deep dreaming and image generation with Caffe and CNNs

DeepDreaming with TensorFlow

deepdraw

Understanding Deep Dreams

Generating Deep Dreams

Audio Deepdream: Optimizing Raw Audio With Convolutional Networks

Image Stylization

Automatic Portrait Segmentation for Image Stylization

Transfiguring Portraits

Stylize Aesthetic QR Code

Published: 09 Oct 2015

Segmentation

Papers

Published: 09 Oct 2015