Deep learning from temporal coherence in video

Gradient-based learning applied to document recognition

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SIGNATURE VERIFICATION USING A “SIAMESE” TIME DELAY NEURAL NETWORK

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Signature Verification Using A "Siamese" Time Delay Neural Network

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Learning by Aligning Videos in Time

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Self-Supervised Learning of Video-Induced Visual Invariances

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Siamese Neural Network-Based Supervised Slow Feature Extraction for Soft Sensor Application

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Fracking Deep Convolutional Image DescriptorsPreprint

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Learning to Linearize Under UncertaintyPreprint

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A Review of Predictive and Contrastive Self-supervised Learning for Medical Images

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The Machine Learning Algorithm as Creative Musical Tool

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Learning Sight from Sound: Ambient Sound Provides Supervision for Visual Learning

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Convolutional long short term memory deep neural networks for image sequence prediction

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OS2D: One-Stage One-Shot Object Detection by Matching Anchor Features

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Robust Cross-Modal Representation Learning with Progressive Self-Distillation

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Semi-Supervised Learning for Surface EMG-based Gesture Recognition

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Correntropy-based robust multilayer extreme learning machines

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Self-Supervised Learning via Conditional Motion Propagation

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Deep learning of invariant spatio-temporal features from video

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A novel deep learning algorithm for incomplete face recognition: Low-rank-recovery network

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Less is More: Surgical Phase Recognition with Less Annotations through Self-Supervised Pre-training of CNN-LSTM NetworksPreprint

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Learning invariance through imitation

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Deep Learning for Data Modeling of Multirate Quality Variables in Industrial Processes

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Temporal Coherency based Criteria for Predicting Video Frames using Deep Multi-stage Generative Adversarial Networks

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A convolutional neural network approach for face verification

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Colorization as a Proxy Task for Visual UnderstandingPreprint

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Multi-View Gait Recognition Based on a Spatial-Temporal Deep Neural Network

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Robust single-view instance recognition

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The Challenges of Continuous Self-Supervised Learning

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Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding

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Learning by coincidence: Siamese networks and common variable learning

Shaham, U., & Lederman, R. R. (2017) · Pattern Recognition · doi:10.1016/j.patcog.2017.09.015 · Cited by 38

Unsupervised Learning using Sequential Verification for Action Recognition.Preprint

Misra, I., Zitnick, C. L., & Hebert, M. (2016) · arXiv (Cornell University) · Cited by 38

Self-taught learning of a deep invariant representation for visual tracking via temporal slowness principle

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Time-Agnostic Prediction: Predicting Predictable Video FramesPreprint

Jayaraman, D., Ebert, F., Efros, A. A., & Levine, S. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1808.07784 · Cited by 37

Nonlinear independent component analysis for principled disentanglement in unsupervised deep learning

Hyvärinen, A., Khemakhem, I., & Morioka, H. (2023) · Patterns · doi:10.1016/j.patter.2023.100844 · Cited by 54

Facial smile detection based on deep learning features

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Deep signatures for indexing and retrieval in large motion databases

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Can Ground Truth Label Propagation from Video Help Semantic Segmentation?

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DiscrimNet: Semi-Supervised Action Recognition from Videos using Generative Adversarial NetworksPreprint

Ahsan, U., Sun, C., & Essa, I. A. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1801.07230 · Cited by 52

Image Patch Matching Using Convolutional Descriptors with Euclidean Distance

Melekhov, I., Kannala, J., & Rahtu, E. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-54526-4_46 · Cited by 33

Generic Object Recognition with Local Receptive Fields Based Extreme Learning Machine

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Object-Centric Representation Learning from Unlabeled Videos

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An Accurate LSTM Based Video Heart Rate Estimation Method

Bian, M., Peng, B., Wang, W., & Dong, J. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-31726-3_35 · Cited by 30

Pose-Sensitive Embedding by Nonlinear NCA Regression

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Regularizing Deep Networks by Modeling and Predicting Label Structure

Mostajabi, M., Maire, M., & Shakhnarovich, G. (2018) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2018.00590 · Cited by 31

Time-Contrastive Learning Based Deep Bottleneck Features for Text-Dependent Speaker Verification

Sarkar, A. K., Tan, Z., Tang, H., Shon, S., & Glass, J. R. (2019) · IEEE/ACM Transactions on Audio Speech and Language Processing · doi:10.1109/taslp.2019.2915322 · Cited by 29

GVSUM: generic video summarization using deep visual features

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Self-Supervised Learning for Facial Action Unit Recognition through Temporal Consistency

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Unsupervised Feature Learning from Temporal DataPreprint

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Learning Image Representations Tied to Egomotion from Unlabeled Video

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Unified Mask Embedding and Correspondence Learning for Self-Supervised Video Segmentation

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Seeing through the blur

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Improving classifiers with unlabeled weakly-related videos

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Learning to Align Sequential Actions in the Wild

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Step-by-step Erasion, One-by-one Collection: A Weakly Supervised Temporal Action DetectorPreprint

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Efficient Representation of Low-Dimensional Manifolds using Deep NetworksPreprint

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Unsupervised Learning of Video Representations via Dense Trajectory Clustering

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Timestamp-Supervised Action Segmentation with Graph Convolutional Networks

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Deep and Modular Neural Networks

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A new 3D convolutional neural network (3D-CNN) framework for multimedia event detection

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Deep Learning for Single-View Instance RecognitionPreprint

Held, D., Thrun, S., & Savarese, S. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1507.08286 · Cited by 26

Automatic Curation of Golf Highlights Using Multimodal Excitement Features

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Autoregressive Predictive Coding: A Comprehensive Study

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Comparison of Data Set Bias in Object Recognition Benchmarks

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Unsupervised Learning of Face Representations

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Dana36: A Multi-camera Image Dataset for Object Identification in Surveillance Scenarios

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Anticipating Where People will Look Using Adversarial Networks

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Coincidence, Categorization, and Consolidation: Learning to Recognize Sounds with Minimal Supervision

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Efficient Discrimination and Localization of Multimodal Remote Sensing Images Using CNN-Based Prediction of Localization Uncertainty

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XBNet: An extremely boosted neural network

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Unsupervised learning from videos using temporal coherency deep networks

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Automated Detection of Animals in Context to Indian Scenario

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Layer-wise analysis of deep networks with Gaussian kernels

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Semisupervised Feature Learning by Deep Entropy-Sparsity Subspace Clustering

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Exploiting Temporal Coherence for Self-Supervised One-Shot Video Re-identification

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To Create What You Tell: Generating Videos from CaptionsPreprint

Pan, Y., Qiu, Z., Yao, T., Li, H., & Mei, T. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1804.08264 · Cited by 26

Cognitive Architectures for Sensory Processing

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Correlation-Based Deep Learning for Multimedia Semantic Concept Detection

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Deep Variation Transformation Network for Foreground Detection

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Hierarchical Modified Fast R-CNN for Object Detection

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Modeling Multiple Views via Implicitly Preserving Global Consistency and Local Complementarity

Li, J., Qiang, W., Zheng, C., Su, B., Razzak, F., Wen, J.-R., & Xiong, H. (2022) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2022.3198746 · Cited by 16

Walking on Minimax Paths for k-NN Search

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Exploiting Spatio-Temporal Structure With Recurrent Winner-Take-All Networks

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Training Conditional Random Fields Using Transfer Learning for Gesture Recognition

Liu, J., Yu, K., Zhang, Y., & Huang, Y. (2010) · Proceedings · doi:10.1109/icdm.2010.31 · Cited by 15

Improving Object Classification using Pose Information

Penedones, H., Collobert, R., Fleuret, F., & Grangier, D. (2012) · Infoscience (Ecole Polytechnique Fédérale de Lausanne) · Cited by 14

Partial-copy detection of non-simulated videos using learning at decision level

Guzman-Zavaleta, Z. J., & Feregrino-Uribe, C. (2018) · Multimedia Tools and Applications · doi:10.1007/s11042-018-6345-2 · Cited by 14

Pose from Action: Unsupervised Learning of Pose Features based on MotionPreprint

Purushwalkam, S., & Gupta, A. K. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1609.05420 · Cited by 14

Adaptive feature learning CNN for behavior recognition in crowd scene

Shuaibu, A. N., Malik, A. S., & Faye, I. (2017) · IEEE International Conference on Signal and Image Processing Applications (ICSIPA) · doi:10.1109/icsipa.2017.8120636 · Cited by 12

Temporally Coherent Visual Representations for Dimensional Affect Recognition

Tellamekala, M. K., & Valstar, M. (2019) · International Conference on Affective Computing and Intelligent Interaction and workshops · doi:10.1109/acii.2019.8925529 · Cited by 13

Self-Supervised Learning for Spinal MRIsPreprint

Jamaludin, A., Kadir, T., & Zisserman, A. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1708.00367 · Cited by 15

Temporal Transductive Inference for Few-Shot Video Object Segmentation

Siam, M. (2025) · International Journal of Computer Vision · doi:10.1007/s11263-025-02390-x · Cited by 14

Hierarchical spatiotemporal feature extraction using recurrent online clustering

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Semi-supervised tuning from temporal coherence

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Dimension Reduction and Construction of Feature Space for Image Pattern Recognition

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Self-Supervised Long-Short Term Memory Network for Solving Complex Job Shop Scheduling Problem

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A generic framework for Generation of Summarized Video Clips using Transfer Learning (SumVClip)

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Remote Sensing Image Recognition Based on LOG-T-SSA-LSSVM and AE-ELM Network

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Learning motion and content-dependent features with convolutions for action recognition

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Learning Representations for Steganalysis from Regularized CNN Model with Auxiliary Tasks

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A Deep-Learning Enabled Traffic Analysis Engine for Video Source Identification

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Restricted Boltzmann Machines Based Fault Estimation in Multi Terminal HVDC Transmission System

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Active Distance-Based Clustering Using K-Medoids

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A Survey on Deep Domain Adaptation and Tiny Object Detection Challenges, Techniques and DatasetsPreprint

Muzammul, M., & Li, X. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2107.07927 · Cited by 19

Unsupervised learning from videos using temporal coherency deep networks

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