On the public citation graph
Harnessing Object and Scene Semantics for Large-Scale Video Understanding
0 signed · 125 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.
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known work and none has been retracted — and get a dated CiteStamped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.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-319-10590-1_53openalex-snapshot
Visualizing and Understanding Convolutional Networks
inferredcites →https://doi.org/10.1007/978-3-319-10605-2_27openalex-snapshot
Reasoning about Object Affordances in a Knowledge Base Representation
inferredcites →https://doi.org/10.1007/978-3-642-15549-9_36openalex-snapshot
Object, Scene and Actions: Combining Multiple Features for Human Action Recognition
inferredcites →https://doi.org/10.1007/978-3-642-33786-4_5openalex-snapshot
Similarity Constrained Latent Support Vector Machine: An Application to Weakly Supervised Action Classification
inferredcites →https://doi.org/10.1007/s11263-013-0636-xopenalex-snapshot
Image Classification with the Fisher Vector: Theory and Practice
inferredcites →https://doi.org/10.1007/s13735-012-0024-2openalex-snapshot
High-level event recognition in unconstrained videos
inferredcites →https://doi.org/10.1037//0033-295x.94.2.115openalex-snapshot
Recognition-by-components: A theory of human image understanding.
inferredcites →https://doi.org/10.1109/cvpr.2009.5206848openalex-snapshot
ImageNet: A large-scale hierarchical image database
inferredcites →https://doi.org/10.1109/cvpr.2010.5540121openalex-snapshot
What helps where – and why? Semantic relatedness for knowledge transfer
inferredcites →https://doi.org/10.1109/cvpr.2012.6247806openalex-snapshot
Action bank: A high-level representation of activity in video
inferredcites →https://doi.org/10.1109/cvpr.2012.6247814openalex-snapshot
Multimodal feature fusion for robust event detection in web videos
inferredcites →https://doi.org/10.1109/cvpr.2013.105openalex-snapshot
Designing Category-Level Attributes for Discriminative Visual 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.2014.81openalex-snapshot
Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
inferredcites →https://doi.org/10.1109/cvpr.2015.7298599openalex-snapshot
What do 15,000 object categories tell us about classifying and localizing actions?
inferredcites →https://doi.org/10.1109/cvpr.2015.7298698openalex-snapshot
ActivityNet: A large-scale video benchmark for human activity understanding
inferredcites →https://doi.org/10.1109/cvpr.2015.7298839openalex-snapshot
Can humans fly? Action understanding with multiple classes of actors
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.2015.7299101openalex-snapshot
Beyond short snippets: Deep networks for video classification
inferredcites →https://doi.org/10.1109/cvpr.2016.576openalex-snapshot
Semi-supervised Vocabulary-Informed Learning
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.2015.510openalex-snapshot
Learning Spatiotemporal Features with 3D Convolutional Networks
inferredcites →https://doi.org/10.1109/tpami.2011.158openalex-snapshot
Weakly Supervised Learning of Interactions between Humans and Objects
inferredcites →https://doi.org/10.1109/tpami.2013.128openalex-snapshot
Learning Multimodal Latent Attributes
inferredcites →https://doi.org/10.1109/tpami.2013.140openalex-snapshot
Attribute-Based Classification for Zero-Shot Visual Object Categorization
inferredcites →https://doi.org/10.1109/tpami.2017.2670560openalex-snapshot
Exploiting Feature and Class Relationships in Video Categorization with Regularized Deep Neural Networks
inferredcites →https://doi.org/10.1109/wacv.2013.6475038openalex-snapshot
Video event recognition using concept attributes
inferredcites →https://doi.org/10.1145/2733373.2806222openalex-snapshot
Modeling Spatial-Temporal Clues in a Hybrid Deep Learning Framework for Video Classification
inferredcites →https://doi.org/10.1184/r1/6475985openalex-snapshot
Object Bank: A High-Level Image Representation for Scene Classification & Semantic Feature Sparsification
inferredcites →https://doi.org/10.3115/v1/d14-1162openalex-snapshot
Glove: Global Vectors for Word Representation
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.1310.4546openalex-snapshot
Distributed Representations of Words and Phrases and their Compositionality
inferredcites →https://doi.org/10.48550/arxiv.1312.5650openalex-snapshot
Zero-Shot Learning by Convex Combination of Semantic Embeddings
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.1409.1556openalex-snapshot
Very Deep Convolutional Networks for Large-Scale Image Recognition
inferredcites →https://doi.org/10.48550/arxiv.1411.5879openalex-snapshot
A Unified Semantic Embedding: Relating Taxonomies and Attributes
inferredcites →https://doi.org/10.48550/arxiv.1412.6856openalex-snapshot
Object Detectors Emerge in Deep Scene CNNs
inferredcites →https://doi.org/10.7551/mitpress/1113.003.0008openalex-snapshot
Probabilities for SV Machines
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-030-01228-1_25openalex-snapshot
Videos as Space-Time Region Graphs
inferred← citeshttps://doi.org/10.1007/978-3-030-05716-9_3openalex-snapshot
Visual Urban Perception with Deep Semantic-Aware Network
inferred← citeshttps://doi.org/10.1007/978-3-030-58607-2_9openalex-snapshot
Take an Emotion Walk: Perceiving Emotions from Gaits Using Hierarchical Attention Pooling and Affective Mapping
inferred← citeshttps://doi.org/10.1007/978-3-319-57021-1_19openalex-snapshot
Deep Learning for Action and Gesture Recognition in Image Sequences: A Survey
inferred← citeshttps://doi.org/10.1007/978-981-15-2109-6_6openalex-snapshot
Group Behavior Recognition
inferred← citeshttps://doi.org/10.1007/s00371-020-01931-4openalex-snapshot
Auxiliary criterion conversion via spatiotemporal semantic encoding and feature entropy for action recognition
inferred← citeshttps://doi.org/10.1007/s10462-018-9651-1openalex-snapshot
Video benchmarks of human action datasets: a review
inferred← citeshttps://doi.org/10.1007/s11042-018-6151-xopenalex-snapshot
A scene image classification technique for a ubiquitous visual surveillance system
inferred← citeshttps://doi.org/10.1007/s11042-023-16566-5openalex-snapshot
Tell me what you see: A zero-shot action recognition method based on natural language descriptions
inferred← citeshttps://doi.org/10.1007/s11263-021-01454-yopenalex-snapshot
Object Priors for Classifying and Localizing Unseen Actions
inferred← citeshttps://doi.org/10.1007/s11263-023-01846-2openalex-snapshot
Universal Prototype Transport for Zero-Shot Action Recognition and Localization
inferred← citeshttps://doi.org/10.1007/s13042-021-01401-wopenalex-snapshot
Deep semantic-aware network for zero-shot visual urban perception
inferred← citeshttps://doi.org/10.1016/j.cviu.2023.103854openalex-snapshot
Scene adaptive mechanism for action recognition
inferred← citeshttps://doi.org/10.1016/j.cviu.2023.103911openalex-snapshot
Hierarchical compositional representations for few-shot action recognition
inferred← citeshttps://doi.org/10.1016/j.eswa.2017.02.026openalex-snapshot
Hierarchically linked infinite hidden Markov model based trajectory analysis and semantic region retrieval in a trajectory dataset
inferred← citeshttps://doi.org/10.1016/j.eswa.2020.113689openalex-snapshot
STCCD: Semantic trajectory clustering based on community detection in networks
inferred← citeshttps://doi.org/10.1016/j.imavis.2026.106093openalex-snapshot
Explicitly modeling trajectories and correlations for video analysis
inferred← citeshttps://doi.org/10.1016/j.mlwa.2022.100278openalex-snapshot
Zero-shot image classification using coupled dictionary embedding
inferred← citeshttps://doi.org/10.1016/j.neucom.2021.01.036openalex-snapshot
Zero-shot action recognition in videos: A survey
inferred← citeshttps://doi.org/10.1016/j.procs.2021.09.287openalex-snapshot
Hybrid Deep Learning Vision-based Models for Human Object Interaction Detection by Knowledge Distillation
inferred← citeshttps://doi.org/10.1038/s41598-025-95465-1openalex-snapshot
Construction of a multiscale feature fusion model for indoor scene recognition and semantic segmentation
inferred← citeshttps://doi.org/10.1109/access.2019.2891745openalex-snapshot
Exploring Object-Centric and Scene-Centric CNN Features and Their Complementarity for Human Rights Violations Recognition in Images
inferred← citeshttps://doi.org/10.1109/acii.2017.8273659openalex-snapshot
Learning based visual engagement and self-efficacy
inferred← citeshttps://doi.org/10.1109/cvpr.2016.120openalex-snapshot
Summary Transfer: Exemplar-Based Subset Selection for Video Summarization
inferred← citeshttps://doi.org/10.1109/cvpr.2016.576openalex-snapshot
Semi-supervised Vocabulary-Informed Learning
inferred← citeshttps://doi.org/10.1109/cvpr.2017.338openalex-snapshot
SCC: Semantic Context Cascade for Efficient Action Detection
inferred← citeshttps://doi.org/10.1109/cvpr.2018.00251openalex-snapshot
Learning to Generate Time-Lapse Videos Using Multi-stage Dynamic Generative Adversarial Networks
inferred← citeshttps://doi.org/10.1109/cvpr.2018.00983openalex-snapshot
Towards Universal Representation for Unseen Action Recognition
inferred← citeshttps://doi.org/10.1109/cvpr52688.2022.01935openalex-snapshot
Crossmodal Representation Learning for Zero-shot Action Recognition
inferred← citeshttps://doi.org/10.1109/cvprw.2017.281openalex-snapshot
Exploring Contextual Engagement for Trauma Recovery
inferred← citeshttps://doi.org/10.1109/dsc67331.2025.00077openalex-snapshot
Dense Crowd Hazard Behavior Recognition Method Based on Semantic-Density Fusion Transformer with Dual Branch Feature Fusion Mechanism
inferred← citeshttps://doi.org/10.1109/iccv.2017.394openalex-snapshot
Leveraging Weak Semantic Relevance for Complex Video Event Classification
inferred← citeshttps://doi.org/10.1109/iccv.2017.476openalex-snapshot
Spatial-Aware Object Embeddings for Zero-Shot Localization and Classification of Actions
inferred← citeshttps://doi.org/10.1109/iccv.2017.622openalex-snapshot
The “Something Something” Video Database for Learning and Evaluating Visual Common Sense
inferred← citeshttps://doi.org/10.1109/iccvw.2017.46openalex-snapshot
Adaptive Pooling in Multi-instance Learning for Web Video Annotation
inferred← citeshttps://doi.org/10.1109/iccvw60793.2023.00039openalex-snapshot
Video Attribute Prototype Network: A New Perspective for Zero-Shot Video Classification
inferred← citeshttps://doi.org/10.1109/icpr.2018.8545513openalex-snapshot
From Text to Video: Exploiting Mid-Level Semantics for Large-Scale Video Classification
inferred← citeshttps://doi.org/10.1109/icra.2019.8793709openalex-snapshot
Unsupervised Out-of-context Action Understanding
inferred← citeshttps://doi.org/10.1109/msp.2017.2763441openalex-snapshot
Recent Advances in Zero-Shot Recognition: Toward Data-Efficient Understanding of Visual Content
inferred← citeshttps://doi.org/10.1109/sibgrapi.2018.00020openalex-snapshot
Object-Based Temporal Segment Relational Network for Activity Recognition
inferred← citeshttps://doi.org/10.1109/tcsvt.2018.2889514openalex-snapshot
Unsupervised Video Action Clustering via Motion-Scene Interaction Constraint
inferred← citeshttps://doi.org/10.1109/tcsvt.2021.3075470openalex-snapshot
Learning Video Moment Retrieval Without a Single Annotated Video
inferred← citeshttps://doi.org/10.1109/tcsvt.2023.3272627openalex-snapshot
Learning Spatio-Temporal Semantics and Cluster Relation for Zero-Shot Action Recognition
inferred← citeshttps://doi.org/10.1109/tcsvt.2024.3423402openalex-snapshot
Video Visualization and Visual Analytics: A Task-Based and Application- Driven Investigation
inferred← citeshttps://doi.org/10.1109/tcyb.2017.2657692openalex-snapshot
Nyström Approximated Temporally Constrained Multisimilarity Spectral Clustering Approach for Movie Scene Detection
inferred← citeshttps://doi.org/10.1109/tip.2018.2814344openalex-snapshot
Self-Supervised Video Hashing With Hierarchical Binary Auto-Encoder
inferred← citeshttps://doi.org/10.1109/tip.2019.2952088openalex-snapshot
A Context Knowledge Map Guided Coarse-to-Fine Action Recognition
inferred← citeshttps://doi.org/10.1109/tmm.2017.2671414openalex-snapshot
VRFP: On-the-Fly Video Retrieval Using Web Images and Fast Fisher Vector Products
inferred← citeshttps://doi.org/10.1109/tmm.2018.2844101openalex-snapshot
Hierarchical Concept Score Postprocessing and Concept-Wise Normalization in CNN-Based Video Event Recognition
inferred← citeshttps://doi.org/10.1109/tmm.2018.2875357openalex-snapshot
Distribution-Oriented Aesthetics Assessment With Semantic-Aware Hybrid Network
inferred← citeshttps://doi.org/10.1109/tmm.2019.2907453openalex-snapshot
Exploiting Mid-Level Semantics for Large-Scale Complex Video Classification
inferred← citeshttps://doi.org/10.1109/tmm.2019.2959426openalex-snapshot
Spatio-Temporal VLAD Encoding of Visual Events Using Temporal Ordering of the Mid-Level Deep Semantics
inferred← citeshttps://doi.org/10.1109/tmm.2020.2969787openalex-snapshot
CI-GNN: Building a Category-Instance Graph for Zero-Shot Video Classification
inferred← citeshttps://doi.org/10.1109/tmm.2021.3050058openalex-snapshot
SAM: Modeling Scene, Object and Action With Semantics Attention Modules for Video Recognition
inferred← citeshttps://doi.org/10.1109/tmm.2024.3386339openalex-snapshot
A Knowledge-Based Hierarchical Causal Inference Network for Video Action Recognition
inferred← citeshttps://doi.org/10.1109/tpami.2019.2922175openalex-snapshot
Vocabulary-Informed Zero-Shot and Open-Set Learning
inferred← citeshttps://doi.org/10.1109/tpami.2020.2985708openalex-snapshot
Learning to Model Relationships for Zero-Shot Video Classification
inferred← citeshttps://doi.org/10.1145/2964284.2964328openalex-snapshot
Multi-Stream Multi-Class Fusion of Deep Networks for Video Classification
inferred← citeshttps://doi.org/10.1145/2964284.2967199openalex-snapshot
Exploiting Objects with LSTMs for Video Categorization
inferred← citeshttps://doi.org/10.1145/3123266.3123379openalex-snapshot
Learning Semantic Feature Map for Visual Content Recognition
inferred← citeshttps://doi.org/10.1145/3231739openalex-snapshot
Visual Content Recognition by Exploiting Semantic Feature Map with Attention and Multi-task Learning
inferred← citeshttps://doi.org/10.1145/3265987.3265989openalex-snapshot
Learning to Detect, Associate, and Recognize Human Actions and Surrounding Scenes in Untrimmed Videos
inferred← citeshttps://doi.org/10.1145/3394171.3413502openalex-snapshot
Depth Guided Adaptive Meta-Fusion Network for Few-shot Video Recognition
inferred← citeshttps://doi.org/10.1145/3394171.3413618openalex-snapshot
Modeling Temporal Concept Receptive Field Dynamically for Untrimmed Video Analysis
inferred← citeshttps://doi.org/10.1145/3394171.3413954openalex-snapshot
Towards More Explainability: Concept Knowledge Mining Network for Event Recognition
inferred← citeshttps://doi.org/10.1145/3394486.3403072openalex-snapshot
Grounding Visual Concepts for Zero-Shot Event Detection and Event Captioning
inferred← citeshttps://doi.org/10.1145/3474085.3475557openalex-snapshot
Sensor-Augmented Egocentric-Video Captioning with Dynamic Modal Attention
inferred← citeshttps://doi.org/10.1145/3503161.3548008openalex-snapshot
Zero-shot Video Classification with Appropriate Web and Task Knowledge Transfer
inferred← citeshttps://doi.org/10.1609/aaai.v34i07.6983openalex-snapshot
Knowledge Integration Networks for Action Recognition
inferred← citeshttps://doi.org/10.1609/aaai.v34i07.6988openalex-snapshot
Find Objects and Focus on Highlights: Mining Object Semantics for Video Highlight Detection via Graph Neural Networks
inferred← citeshttps://doi.org/10.23919/mva65244.2025.11175123openalex-snapshot
MoExDA: Domain Adaptation for Edge-based Action Recognition
inferred← citeshttps://doi.org/10.3390/s19194237openalex-snapshot
An Unsupervised Framework for Online Spatiotemporal Detection of Activities of Daily Living by Hierarchical Activity Models
inferred← citeshttps://doi.org/10.48550/arxiv.1707.06436openalex-snapshot
cvpaper.challenge in 2016: Futuristic Computer Vision through 1,600 Papers Survey
inferred← citeshttps://doi.org/10.48550/arxiv.1710.04837openalex-snapshot
Recent Advances in Zero-shot Recognition
inferred← citeshttps://doi.org/10.48550/arxiv.1801.09184openalex-snapshot
Contextual Multi-Scale Region Convolutional 3D Network for Activity Detection
inferred← citeshttps://doi.org/10.48550/arxiv.1802.06971openalex-snapshot
A survey on trajectory clustering analysis
inferred← citeshttps://doi.org/10.48550/arxiv.1905.10654openalex-snapshot
Exploring Temporal Information for Improved Video Understanding
inferred← citeshttps://doi.org/10.48550/arxiv.1912.11861openalex-snapshot
A Review on Intelligent Object Perception Methods Combining Knowledge-based Reasoning and Machine Learning
inferred← citeshttps://doi.org/10.48550/arxiv.2012.06567openalex-snapshot
A Comprehensive Study of Deep Video Action Recognition
inferred← citeshttps://doi.org/10.5244/c.35.213openalex-snapshot
Zero-Shot Action Recognition from Diverse Object-Scene Compositions
inferred← citeshttps://doi.org/10.70675/ab9825adz1fb8z4f1cz9217zef67d5530022openalex-snapshot
Spatial techniques for video understanding
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.