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Look, Listen, and Attend: Co-Attention Network for Self-Supervised Audio-Visual Representation Learning

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What this work says

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

inferredcites →https://doi.org/10.1007/978-3-030-01231-1_39openalex-snapshot

Audio-Visual Scene Analysis with Self-Supervised Multisensory Features

inferredcites →https://doi.org/10.1007/978-3-030-01246-5_27openalex-snapshot

Objects that Sound

inferredcites →https://doi.org/10.1007/978-3-030-01246-5_35openalex-snapshot

The Sound of Pixels

inferredcites →https://doi.org/10.1007/978-3-030-01267-0_19openalex-snapshot

Rethinking Spatiotemporal Feature Learning: Speed-Accuracy Trade-offs in Video Classification

inferredcites →https://doi.org/10.1007/978-3-319-10605-2_45openalex-snapshot

Movement Pattern Histogram for Action Recognition and Retrieval

inferredcites →https://doi.org/10.1007/978-3-319-46448-0_48openalex-snapshot

Ambient Sound Provides Supervision for Visual Learning

inferredcites →https://doi.org/10.1007/s10462-016-9473-yopenalex-snapshot

A review on human action analysis in videos for retrieval applications

inferredcites →https://doi.org/10.1109/avss.2010.63openalex-snapshot

MuHAVi: A Multicamera Human Action Video Dataset for the Evaluation of Action Recognition Methods

inferredcites →https://doi.org/10.1109/cvpr.2005.274openalex-snapshot

Pixels that Sound

inferredcites →https://doi.org/10.1109/cvpr.2007.383344openalex-snapshot

Harmony in Motion

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.2016.319openalex-snapshot

Learning Deep Features for Discriminative Localization

inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot

Deep Residual Learning for Image Recognition

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.2018.00675openalex-snapshot

A Closer Look at Spatiotemporal Convolutions for Action Recognition

inferredcites →https://doi.org/10.1109/cvpr.2019.00947openalex-snapshot

Deep Multimodal Clustering for Unsupervised Audiovisual Learning

inferredcites →https://doi.org/10.1109/icassp.2017.7952261openalex-snapshot

Audio Set: An ontology and human-labeled dataset for audio events

inferredcites →https://doi.org/10.1109/icassp.2019.8682524openalex-snapshot

Perfect Match: Improved Cross-modal Embeddings for Audio-visual Synchronisation

inferredcites →https://doi.org/10.1109/icassp.2019.8682863openalex-snapshot

Dynamic Temporal Alignment of Speech to Lips

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

Learning Spatiotemporal Features with 3D Convolutional Networks

inferredcites →https://doi.org/10.1109/iccv.2017.73openalex-snapshot

Look, Listen and Learn

inferredcites →https://doi.org/10.1109/iccvw.2015.95openalex-snapshot

Seeing the Sound: A New Multimodal Imaging Device for Computer Vision

inferredcites →https://doi.org/10.1109/tip.2006.891352openalex-snapshot

Semantic-Based Surveillance Video Retrieval

inferredcites →https://doi.org/10.1109/tmm.2012.2228476openalex-snapshot

Multimodal Analysis for Identification and Segmentation of Moving-Sounding Objects

inferredcites →https://doi.org/10.1109/tpami.2012.59openalex-snapshot

3D Convolutional Neural Networks for Human Action Recognition

inferredcites →https://doi.org/10.1109/tpami.2015.2430335openalex-snapshot

Anticipating Human Activities Using Object Affordances for Reactive Robotic Response

inferredcites →https://doi.org/10.1145/2696454.2696462openalex-snapshot

Robot-Centric Activity Prediction from First-Person Videos

What points at this work

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

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QDFormer: Towards Robust Audiovisual Segmentation in Complex Environments with Quantization-based Semantic Decomposition

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AVF-MAE++: Scaling Affective Video Facial Masked Autoencoders via Efficient Audio-Visual Self-Supervised Learning

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Audio-Visual Generalized Zero-Shot Learning using Pre-Trained Large Multi-Modal Models

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Enhancing Contrastive Learning with Temporal Cognizance for Audio-Visual Representation Generation

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Cross-Modal Audio-Visual Co-Learning for Text-Independent Speaker Verification

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Self-Supervised Contrastive Learning for Audio-Visual Action Recognition

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Scalable Audiovisual Masked Autoencoders for Efficient Affective Video Facial Analysis

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