On the public citation graph

Spatio-Temporal Reconstruction of Video Frames for Efficient Real-Time Deepfake Detection

https://doi.org/10.2139/ssrn.7067177
0 signed · 21 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 See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.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/10.1002/eng2.70087openalex-snapshot
Audio Deepfake Detection Using Deep Learning
inferredcites →https://doi.org/10.1007/s00521-024-10181-7openalex-snapshot
Deepfake detection using convolutional vision transformers and convolutional neural networks
inferredcites →https://doi.org/10.1007/s11760-025-03970-7openalex-snapshot
Enhancing multimodal deepfake detection with local–global feature integration and diffusion models
inferredcites →https://doi.org/10.1007/s13369-025-10526-xopenalex-snapshot
Deepfake Detection in CCTV Videos Using Deep Learning
inferredcites →https://doi.org/10.1007/s42979-021-00495-xopenalex-snapshot
A Machine Learning Based Approach for Deepfake Detection in Social Media Through Key Video Frame Extraction
inferredcites →https://doi.org/10.1016/j.asoc.2025.112974openalex-snapshot
Exploring coordinated motion patterns of facial landmarks for deepfake video detection
inferredcites →https://doi.org/10.1016/j.inffus.2024.102424openalex-snapshot
Triple-modality interaction for deepfake detection on zero-shot identity
inferredcites →https://doi.org/10.1049/bme2.12031openalex-snapshot
A Survey on Deepfake Video Detection
inferredcites →https://doi.org/10.1057/s41599-025-05389-4openalex-snapshot
Leveraging data analytics for detection and impact evaluation of fake news and deepfakes in social networks
inferredcites →https://doi.org/10.1109/tcsvt.2021.3074259openalex-snapshot
Detecting Compressed Deepfake Videos in Social Networks Using Frame-Temporality Two-Stream Convolutional Network
inferredcites →https://doi.org/10.1109/tcsvt.2023.3278310openalex-snapshot
FAMM: Facial Muscle Motions for Detecting Compressed Deepfake Videos Over Social Networks
inferredcites →https://doi.org/10.1109/tifs.2023.3239223openalex-snapshot
ISTVT: Interpretable Spatial-Temporal Video Transformer for Deepfake Detection
inferredcites →https://doi.org/10.1109/tifs.2023.3262148openalex-snapshot
AVoiD-DF: Audio-Visual Joint Learning for Detecting Deepfake
inferredcites →https://doi.org/10.1109/tkde.2019.2912815openalex-snapshot
Reliable Accuracy Estimates from k-Fold Cross Validation
inferredcites →https://doi.org/10.1145/3612928openalex-snapshot
Head Pose Estimation Patterns as Deepfake Detectors
inferredcites →https://doi.org/10.1145/3686162openalex-snapshot
Face Reconstruction-Based Generalized Deepfake Detection Model with Residual Outlook Attention
inferredcites →https://doi.org/10.1371/journal.pone.0334980openalex-snapshot
Deepfake defense: Combining spatial and temporal cues with CNN–BiLSTM–transformer architecture
inferredcites →https://doi.org/10.32604/cmc.2025.062922openalex-snapshot
Deepfake Detection Method Based on Spatio-Temporal Information Fusion
inferredcites →https://doi.org/10.3389/fdata.2025.1669488openalex-snapshot
CrossDF: improving cross-domain deepfake detection with deep information decomposition
inferredcites →https://doi.org/10.3390/app15126622openalex-snapshot
GenConViT: Deepfake Video Detection Using Generative Convolutional Vision Transformer
inferredcites →https://doi.org/10.52202/075280-0201openalex-snapshot
DeepfakeBench: A Comprehensive Benchmark of Deepfake Detection
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.