On the public citation graph

DynamoNet: Dynamic Action and Motion Network

https://doi.org/10.1109/iccv.2019.00629

0 signed · 155 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.

Claim with ORCID

Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.

See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-030-01225-0_18openalex-snapshot

Spatio-temporal Channel Correlation Networks for Action Classification

inferredcites →https://doi.org/10.1007/978-3-030-01249-6_19openalex-snapshot

Action Anticipation with RBF Kernelized Feature Mapping RNN

inferredcites →https://doi.org/10.1007/978-3-319-46448-0_32openalex-snapshot

Shuffle and Learn: Unsupervised Learning Using Temporal Order Verification

inferredcites →https://doi.org/10.1007/978-3-319-46484-8_2openalex-snapshot

Temporal Segment Networks: Towards Good Practices for Deep Action Recognition

inferredcites →https://doi.org/10.1007/978-3-319-46493-0_18openalex-snapshot

View Synthesis by Appearance Flow

inferredcites →https://doi.org/10.1007/978-3-319-46493-0_47openalex-snapshot

Attribute2Image: Conditional Image Generation from Visual Attributes

inferredcites →https://doi.org/10.1007/978-3-319-46493-0_51openalex-snapshot

Deep3D: Fully Automatic 2D-to-3D Video Conversion with Deep Convolutional Neural Networks

inferredcites →https://doi.org/10.1007/978-3-642-33374-3_41openalex-snapshot

HMDB51: A Large Video Database for Human Motion Recognition

inferredcites →https://doi.org/10.1109/cvpr.2014.223openalex-snapshot

Large-Scale Video Classification with Convolutional Neural Networks

inferredcites →https://doi.org/10.1109/cvpr.2014.83openalex-snapshot

Multi-view Super Vector for Action Recognition

inferredcites →https://doi.org/10.1109/cvpr.2015.7298878openalex-snapshot

Long-term recurrent convolutional networks for visual recognition and description

inferredcites →https://doi.org/10.1109/cvpr.2015.7299059openalex-snapshot

Action recognition with trajectory-pooled deep-convolutional descriptors

inferredcites →https://doi.org/10.1109/cvpr.2015.7299101openalex-snapshot

Beyond short snippets: Deep networks for video classification

inferredcites →https://doi.org/10.1109/cvpr.2015.7299117openalex-snapshot

A Dynamic Convolutional Layer for short rangeweather prediction

inferredcites →https://doi.org/10.1109/cvpr.2016.18openalex-snapshot

Anticipating Visual Representations from Unlabeled Video

inferredcites →https://doi.org/10.1109/cvpr.2016.213openalex-snapshot

Convolutional Two-Stream Network Fusion for Video Action Recognition

inferredcites →https://doi.org/10.1109/cvpr.2017.168openalex-snapshot

Deep Temporal Linear Encoding Networks

inferredcites →https://doi.org/10.1109/cvpr.2017.291openalex-snapshot

Optical Flow Estimation Using a Spatial Pyramid Network

inferredcites →https://doi.org/10.1109/cvpr.2017.319openalex-snapshot

Generating the Future with Adversarial Transformers

inferredcites →https://doi.org/10.1109/cvpr.2017.337openalex-snapshot

ActionVLAD: Learning Spatio-Temporal Aggregation for Action Classification

inferredcites →https://doi.org/10.1109/cvpr.2017.502openalex-snapshot

Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset

inferredcites →https://doi.org/10.1109/cvpr.2017.607openalex-snapshot

Self-Supervised Video Representation Learning with Odd-One-Out Networks

inferredcites →https://doi.org/10.1109/cvpr.2018.00424openalex-snapshot

Classification-Driven Dynamic Image Enhancement

inferredcites →https://doi.org/10.1109/cvpr.2018.00675openalex-snapshot

A Closer Look at Spatiotemporal Convolutions for Action Recognition

inferredcites →https://doi.org/10.1109/cvpr.2018.00685openalex-snapshot

Can Spatiotemporal 3D CNNs Retrace the History of 2D CNNs and ImageNet?

inferredcites →https://doi.org/10.1109/cvpr.2018.00813openalex-snapshot

Non-local Neural Networks

inferredcites →https://doi.org/10.1109/cvpr.2018.00840openalex-snapshot

Learning and Using the Arrow of Time

inferredcites →https://doi.org/10.1109/fg.2019.8756609openalex-snapshot

Self-Supervised Learning of Face Representations for Video Face Clustering

inferredcites →https://doi.org/10.1109/iccv.2011.6126543openalex-snapshot

HMDB: A large video database for human motion recognition

inferredcites →https://doi.org/10.1109/iccv.2013.441openalex-snapshot

Action Recognition with Improved Trajectories

inferredcites →https://doi.org/10.1109/iccv.2015.123openalex-snapshot

Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

inferredcites →https://doi.org/10.1109/iccv.2015.316openalex-snapshot

FlowNet: Learning Optical Flow with Convolutional Networks

inferredcites →https://doi.org/10.1109/iccv.2015.510openalex-snapshot

Learning Spatiotemporal Features with 3D Convolutional Networks

inferredcites →https://doi.org/10.1109/iccv.2015.522openalex-snapshot

Human Action Recognition Using Factorized Spatio-Temporal Convolutional Networks

inferredcites →https://doi.org/10.1109/iccvw.2017.373openalex-snapshot

Learning Spatio-Temporal Features with 3D Residual Networks for Action Recognition

inferredcites →https://doi.org/10.1109/tpami.2018.2854726openalex-snapshot

Visual Dynamics: Stochastic Future Generation via Layered Cross Convolutional Networks

inferredcites →https://doi.org/10.1109/wacv.2018.00179openalex-snapshot

ActionFlowNet: Learning Motion Representation for Action Recognition

inferredcites →https://doi.org/10.1145/3343031.3351071openalex-snapshot

Self-supervised Face-Grouping on Graphs

inferredcites →https://doi.org/10.13016/m26gih-tnyzopenalex-snapshot

Generating Videos with Scene Dynamics

inferredcites →https://doi.org/10.13016/m26ion-fjjhopenalex-snapshot

Anticipating Visual Representations from Unlabeled Video

inferredcites →https://doi.org/10.3156/jsoft.29.5_177_2openalex-snapshot

GAN（Generative Adversarial Nets）

inferredcites →https://doi.org/10.48550/arxiv.1212.0402openalex-snapshot

UCF-101: A dataset of 101 human actions classes from videos in the wild

inferredcites →https://doi.org/10.48550/arxiv.1406.2199openalex-snapshot

Two-Stream Convolutional Networks for Action Recognition in Videos

inferredcites →https://doi.org/10.48550/arxiv.1502.03167openalex-snapshot

Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

inferredcites →https://doi.org/10.48550/arxiv.1502.04623openalex-snapshot

DRAW: A Recurrent Neural Network For Image Generation

inferredcites →https://doi.org/10.48550/arxiv.1502.04681openalex-snapshot

Unsupervised Learning of Video Representations using LSTMs

inferredcites →https://doi.org/10.48550/arxiv.1511.06434openalex-snapshot

Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks

inferredcites →https://doi.org/10.48550/arxiv.1604.06573openalex-snapshot

Convolutional Two-Stream Network Fusion for Video Action Recognition

inferredcites →https://doi.org/10.48550/arxiv.1608.00182openalex-snapshot

Deep FisherNet for Object Classification

inferredcites →https://doi.org/10.48550/arxiv.1611.02155openalex-snapshot

Spatiotemporal Residual Networks for Video Action Recognition

inferredcites →https://doi.org/10.48550/arxiv.1708.05038openalex-snapshot

ConvNet Architecture Search for Spatiotemporal Feature Learning

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4832892openalex-extracted

Future Frontiers in Deep Learning: From Static to Dynamic Neural Network Technologies

inferred← citeshttps://doi.org/10.1007/978-3-030-58558-7_35openalex-snapshot

Large Scale Holistic Video Understanding

inferred← citeshttps://doi.org/10.1007/978-3-030-58568-6_5openalex-snapshot

Self-supervised Motion Representation via Scattering Local Motion Cues

inferred← citeshttps://doi.org/10.1007/978-3-030-58580-8_19openalex-snapshot

Memory-Augmented Dense Predictive Coding for Video Representation Learning

inferred← citeshttps://doi.org/10.1007/978-3-030-89134-3_21openalex-snapshot

An Abnormal Behavior Recognition Method Based on Fusion Features

inferred← citeshttps://doi.org/10.1007/978-3-031-19778-9_38openalex-snapshot

My View is the Best View: Procedure Learning from Egocentric Videos

inferred← citeshttps://doi.org/10.1007/978-3-031-19821-2_1openalex-snapshot

GOCA: Guided Online Cluster Assignment for Self-supervised Video Representation Learning

inferred← citeshttps://doi.org/10.1007/978-3-031-19833-5_21openalex-snapshot

MaCLR: Motion-Aware Contrastive Learning of Representations for Videos

inferred← citeshttps://doi.org/10.1007/978-3-031-20083-0_24openalex-snapshot

Adaptive Token Sampling for Efficient Vision Transformers

inferred← citeshttps://doi.org/10.1007/978-3-031-25069-9_2openalex-snapshot

MoQuad: Motion-focused Quadruple Construction for Video Contrastive Learning

inferred← citeshttps://doi.org/10.1007/978-3-031-57679-9_6openalex-snapshot

Unsupervised Feature Learning for Video Understanding

inferred← citeshttps://doi.org/10.1007/978-3-031-72973-7_9openalex-snapshot

Learning by Aligning 2D Skeleton Sequences and Multi-modality Fusion

inferred← citeshttps://doi.org/10.1007/978-3-031-73235-5_25openalex-snapshot

ViC-MAE: Self-supervised Representation Learning from Images and Video with Contrastive Masked Autoencoders

inferred← citeshttps://doi.org/10.1007/s00371-024-03638-2openalex-snapshot

A simulated two-stream network via multilevel distillation of reviewed features and decoupled logits for video action recognition

inferred← citeshttps://doi.org/10.1007/s00521-021-06467-9openalex-snapshot

(2+1)D-SLR: an efficient network for video sign language recognition

inferred← citeshttps://doi.org/10.1007/s11042-024-18288-8openalex-snapshot

Efficient ship detection in sar images with dynamic feature smoothing and visual module using omni-dimensional dynamic large-scale convolution

inferred← citeshttps://doi.org/10.1007/s11760-022-02268-2openalex-snapshot

AMA: attention-based multi-feature aggregation module for action recognition

inferred← citeshttps://doi.org/10.1007/s11760-025-03969-0openalex-snapshot

CDPT: context-driven omni-dimensional dynamic pose transfer network

inferred← citeshttps://doi.org/10.1007/s11831-026-10498-7openalex-snapshot

Architectural and Performance Analysis of Static and Dynamic Neural Networks in Plant Disease Detection

inferred← citeshttps://doi.org/10.1007/s13042-021-01301-zopenalex-snapshot

A two-stage temporal proposal network for precise action localization in untrimmed video

inferred← citeshttps://doi.org/10.1007/s13042-024-02368-0openalex-snapshot

Video anomaly detection based on multi-scale optical flow spatio-temporal enhancement and normality mining

inferred← citeshttps://doi.org/10.1016/j.compeleceng.2024.109710openalex-snapshot

Neural network developments: A detailed survey from static to dynamic models

inferred← citeshttps://doi.org/10.1016/j.infrared.2024.105475openalex-snapshot

MDCENet: Multi-Dimensional Cross-Enhanced Network for infrared small target detection

inferred← citeshttps://doi.org/10.1016/j.ins.2021.05.052openalex-snapshot

Graph visual tracking using conditional uncertainty minimization and minibatch Monte Carlo inference

inferred← citeshttps://doi.org/10.1016/j.knosys.2024.112076openalex-snapshot

Video and audio are images: A cross-modal mixer for original data on video–audio retrieval

inferred← citeshttps://doi.org/10.1016/j.neucom.2021.11.031openalex-snapshot

Contrastive predictive coding with transformer for video representation learning

inferred← citeshttps://doi.org/10.1016/j.neunet.2022.11.009openalex-snapshot

DANet: Semi-supervised differentiated auxiliaries guided network for video action recognition

inferred← citeshttps://doi.org/10.1016/j.vrih.2021.05.001openalex-snapshot

Review of dynamic gesture recognition

inferred← citeshttps://doi.org/10.1109/access.2019.2953113openalex-snapshot

SAST: Learning Semantic Action-Aware Spatial-Temporal Features for Efficient Action Recognition

inferred← citeshttps://doi.org/10.1109/access.2020.3043386openalex-snapshot

Temporal Memory Network Towards Real-Time Video Understanding

inferred← citeshttps://doi.org/10.1109/ccisp52774.2021.9639335openalex-snapshot

Home Video Behavior Recognition based on Convolutional Residual Network with Visual Privacy Protection Mechanism and Temporal Adaptive Module

inferred← citeshttps://doi.org/10.1109/cvpr42600.2020.00043openalex-snapshot

Video Modeling With Correlation Networks

inferred← citeshttps://doi.org/10.1109/cvpr42600.2020.00994openalex-snapshot

SpeedNet: Learning the Speediness in Videos

inferred← citeshttps://doi.org/10.1109/cvpr42600.2020.01185openalex-snapshot

Sideways: Depth-Parallel Training of Video Models

inferred← citeshttps://doi.org/10.1109/cvpr46437.2021.00331openalex-snapshot

A Large-Scale Study on Unsupervised Spatiotemporal Representation Learning

inferred← citeshttps://doi.org/10.1109/cvpr46437.2021.00470openalex-snapshot

3D CNNs with Adaptive Temporal Feature Resolutions

inferred← citeshttps://doi.org/10.1109/cvpr46437.2021.00550openalex-snapshot

Learning by Aligning Videos in Time

inferred← citeshttps://doi.org/10.1109/cvpr46437.2021.00689openalex-snapshot

Spatiotemporal Contrastive Video Representation Learning

inferred← citeshttps://doi.org/10.1109/cvpr46437.2021.00748openalex-snapshot

Beyond Short Clips: End-to-End Video-Level Learning with Collaborative Memories

inferred← citeshttps://doi.org/10.1109/cvpr46437.2021.01163openalex-snapshot

Removing the Background by Adding the Background: Towards Background Robust Self-supervised Video Representation Learning

inferred← citeshttps://doi.org/10.1109/cvpr46437.2021.01195openalex-snapshot

DISCO: Dynamic and Invariant Sensitive Channel Obfuscation for deep neural networks

inferred← citeshttps://doi.org/10.1109/cvpr52688.2022.00222openalex-snapshot

Learning to Align Sequential Actions in the Wild

inferred← citeshttps://doi.org/10.1109/cvpr52688.2022.00324openalex-snapshot

Complex Video Action Reasoning via Learnable Markov Logic Network

inferred← citeshttps://doi.org/10.1109/cvpr52688.2022.00800openalex-snapshot

Context-Aware Sequence Alignment using 4D Skeletal Augmentation

inferred← citeshttps://doi.org/10.1109/cvpr52688.2022.00950openalex-snapshot

Hierarchical Self-supervised Representation Learning for Movie Understanding

inferred← citeshttps://doi.org/10.1109/cvpr52688.2022.01345openalex-snapshot

Learning from Untrimmed Videos: Self-Supervised Video Representation Learning with Hierarchical Consistency

inferred← citeshttps://doi.org/10.1109/cvpr52688.2022.01562openalex-snapshot

SLIC: Self-Supervised Learning with Iterative Clustering for Human Action Videos

inferred← citeshttps://doi.org/10.1109/cvpr52688.2022.01954openalex-snapshot

Unsupervised Action Segmentation by Joint Representation Learning and Online Clustering

inferred← citeshttps://doi.org/10.1109/cvprw56347.2022.00458openalex-snapshot

SCVRL: Shuffled Contrastive Video Representation Learning

inferred← citeshttps://doi.org/10.1109/cvprw59228.2023.00160openalex-snapshot

AsConvSR: Fast and Lightweight Super-Resolution Network with Assembled Convolutions

inferred← citeshttps://doi.org/10.1109/iccv48922.2021.00153openalex-snapshot

Vi2CLR: Video and Image for Visual Contrastive Learning of Representation

inferred← citeshttps://doi.org/10.1109/iccv48922.2021.00158openalex-snapshot

Dynamic Context-Sensitive Filtering Network for Video Salient Object Detection

inferred← citeshttps://doi.org/10.1109/iccv48922.2021.00211openalex-snapshot

Motion-Focused Contrastive Learning of Video Representations

inferred← citeshttps://doi.org/10.1109/iccv48922.2021.00871openalex-snapshot

Composable Augmentation Encoding for Video Representation Learning

inferred← citeshttps://doi.org/10.1109/iccv48922.2021.01026openalex-snapshot

Motion-Augmented Self-Training for Video Recognition at Smaller Scale

inferred← citeshttps://doi.org/10.1109/iccv48922.2021.01039openalex-snapshot

Space-Time Crop & Attend: Improving Cross-modal Video Representation Learning

inferred← citeshttps://doi.org/10.1109/iccvw54120.2021.00358openalex-snapshot

Video Contrastive Learning with Global Context

inferred← citeshttps://doi.org/10.1109/iccvw60793.2023.00093openalex-snapshot

Spatio-Temporal Convolution-Attention Video Network

inferred← citeshttps://doi.org/10.1109/iccvw69036.2025.00730openalex-snapshot

Reinforcement Learning Meets Masked Video Modeling : Trajectory-Guided Adaptive Token Selection

inferred← citeshttps://doi.org/10.1109/icpr48806.2021.9412124openalex-snapshot

MFI: Multi-range Feature Interchange for Video Action Recognition

inferred← citeshttps://doi.org/10.1109/itoec57671.2023.10291257openalex-snapshot

Human Action Recognition Based on Residual Networks with Improved Attention Mechanisms

inferred← citeshttps://doi.org/10.1109/jstars.2023.3321963openalex-snapshot

SpatioTemporal Inference Network for Precipitation Nowcasting With Multimodal Fusion

inferred← citeshttps://doi.org/10.1109/lra.2020.3017478openalex-snapshot

Don’t Forget The Past: Recurrent Depth Estimation from Monocular Video

inferred← citeshttps://doi.org/10.1109/tcsvt.2021.3060162openalex-snapshot

Deep Cross-Modal Representation Learning and Distillation for Illumination-Invariant Pedestrian Detection

inferred← citeshttps://doi.org/10.1109/tcsvt.2022.3149329openalex-snapshot

Order-Constrained Representation Learning for Instructional Video Prediction

inferred← citeshttps://doi.org/10.1109/tcsvt.2022.3207174openalex-snapshot

Consistent Intra-Video Contrastive Learning With Asynchronous Long-Term Memory Bank

inferred← citeshttps://doi.org/10.1109/tifs.2025.3531772openalex-snapshot

Collaboratively Self-Supervised Video Representation Learning for Action Recognition

inferred← citeshttps://doi.org/10.1109/tip.2022.3212905openalex-snapshot

A General Dynamic Knowledge Distillation Method for Visual Analytics

inferred← citeshttps://doi.org/10.1109/tip.2022.3222623openalex-snapshot

Compact Representation and Reliable Classification Learning for Point-Level Weakly-Supervised Action Localization

inferred← citeshttps://doi.org/10.1109/tip.2025.3583168openalex-snapshot

Cross-Modal Contrastive Masked AutoEncoder for Compressed Video Pre-Training

inferred← citeshttps://doi.org/10.1109/tmm.2022.3174341openalex-snapshot

MFGNet: Dynamic Modality-Aware Filter Generation for RGB-T Tracking

inferred← citeshttps://doi.org/10.1109/tmm.2022.3189253openalex-snapshot

LgNet: A Local-Global Network for Action Recognition and Beyond

inferred← citeshttps://doi.org/10.1109/tmm.2023.3244126openalex-snapshot

ParamCrop: Parametric Cubic Cropping for Video Contrastive Learning

inferred← citeshttps://doi.org/10.1109/tmm.2023.3292596openalex-snapshot

DSS-Net: Dynamic Self-Supervised Network for Video Anomaly Detection

inferred← citeshttps://doi.org/10.1109/tmm.2023.3293727openalex-snapshot

Self-Supervised Video Representation Learning by Serial Restoration With Elastic Complexity

inferred← citeshttps://doi.org/10.1109/tnnls.2022.3219936openalex-snapshot

Self Supervised Progressive Network for High Performance Video Object Segmentation

inferred← citeshttps://doi.org/10.1109/tpami.2021.3116945openalex-snapshot

VideoDG: Generalizing Temporal Relations in Videos to Novel Domains

inferred← citeshttps://doi.org/10.1109/tpami.2021.3117837openalex-snapshot

Dynamic Neural Networks: A Survey

inferred← citeshttps://doi.org/10.1109/tpami.2023.3273415openalex-snapshot

Self-Supervised Learning from Untrimmed Videos via Hierarchical Consistency

inferred← citeshttps://doi.org/10.1109/tpami.2024.3415112openalex-snapshot

A Survey on Self-Supervised Learning: Algorithms, Applications, and Future Trends

inferred← citeshttps://doi.org/10.1109/wacv51458.2022.00025openalex-snapshot

SSCAP: Self-supervised Co-occurrence Action Parsing for Unsupervised Temporal Action Segmentation

inferred← citeshttps://doi.org/10.1109/wacv51458.2022.00105openalex-snapshot

Hierarchically Decoupled Spatial-Temporal Contrast for Self-supervised Video Representation Learning

inferred← citeshttps://doi.org/10.1109/wacv57701.2024.00638openalex-snapshot

United We Stand, Divided We Fall: UnityGraph for Unsupervised Procedure Learning from Videos

inferred← citeshttps://doi.org/10.1117/12.3010350openalex-snapshot

Implementation of campus supervision system based on Yolov5 and SlowFast optimization model

inferred← citeshttps://doi.org/10.1145/3460426.3463616openalex-snapshot

Local-enhanced Interaction for Temporal Moment Localization

inferred← citeshttps://doi.org/10.1145/3474085.3475278openalex-snapshot

Visual Co-Occurrence Alignment Learning for Weakly-Supervised Video Moment Retrieval

inferred← citeshttps://doi.org/10.1145/3474085.3475394openalex-snapshot

Learning Spatio-temporal Representation by Channel Aliasing Video Perception

inferred← citeshttps://doi.org/10.1145/3483381openalex-snapshot

Adversarial Multi-Grained Embedding Network for Cross-Modal Text-Video Retrieval

inferred← citeshttps://doi.org/10.1145/3583780.3614958openalex-snapshot

Mask- and Contrast-Enhanced Spatio-Temporal Learning for Urban Flow Prediction

inferred← citeshttps://doi.org/10.1145/3664647.3680754openalex-snapshot

MAGIC: Rethinking Dynamic Convolution Design for Medical Image Segmentation

inferred← citeshttps://doi.org/10.1186/s13102-026-01574-3openalex-snapshot

A study on the application of multimodal technologies in personalized training systems for the integration of physical education and general education

inferred← citeshttps://doi.org/10.12677/csa.2020.105102openalex-snapshot

A Review of Vision Based Dynamic Hand Gestures Recognition

inferred← citeshttps://doi.org/10.1609/aaai.v37i3.25416openalex-snapshot

Self-Supervised Video Representation Learning via Latent Time Navigation

inferred← citeshttps://doi.org/10.32657/10356/152209openalex-snapshot

Improving self-supervision in video representation learning

inferred← citeshttps://doi.org/10.48550/arxiv.1912.06640openalex-snapshot

SPIN: A High Speed, High Resolution Vision Dataset for Tracking and Action Recognition in Ping Pong

inferred← citeshttps://doi.org/10.48550/arxiv.2001.05691openalex-snapshot

Learning Spatiotemporal Features via Video and Text Pair Discrimination

inferred← citeshttps://doi.org/10.48550/arxiv.2003.08042openalex-snapshot

STH: Spatio-Temporal Hybrid Convolution for Efficient Action Recognition

inferred← citeshttps://doi.org/10.48550/arxiv.2003.14285openalex-snapshot

Explaining Motion Relevance for Activity Recognition in Video Deep Learning Models

inferred← citeshttps://doi.org/10.48550/arxiv.2009.05769openalex-snapshot

Removing the Background by Adding the Background: Towards Background Robust Self-supervised Video Representation Learning

inferred← citeshttps://doi.org/10.48550/arxiv.2010.09709openalex-snapshot

Self-supervised Co-training for Video Representation Learning

inferred← citeshttps://doi.org/10.48550/arxiv.2102.07887openalex-snapshot

VA-RED$^2$: Video Adaptive Redundancy Reduction

inferred← citeshttps://doi.org/10.48550/arxiv.2201.04029openalex-snapshot

Motion-Focused Contrastive Learning of Video Representations

inferred← citeshttps://doi.org/10.70675/4046013fz7818z4acdza84bze9be293f2334openalex-snapshot

Learning effective video representations for action recognition

inferred← citeshttps://doi.org/10.7717/peerj-cs.317openalex-snapshot

Online supervised attention-based recurrent depth estimation from monocular video

Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.