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Works299 from public data
- Celeb-DF: A Large-Scale Challenging Dataset for DeepFake Forensics1,885
This work presents a new large-scale challenging DeepFake video dataset, Celeb-DF, which contains 5,639 high-quality DeepFake videos of celebrities generated using improved synthesis process and conducts a comprehensive evaluation of DeepFake detection methods and datasets to demonstrate the escalated level of challenges posed by Celebrity-DF.
- Exposing Deep Fakes Using Inconsistent Head Poses1,173
This paper proposes a new method to expose AI-generated fake face images or videos based on the observations that Deep Fakes are created by splicing synthesized face region into the original image, and in doing so, introducing errors that can be revealed when 3D head poses are estimated from the face images.
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- UA-DETRAC: A new benchmark and protocol for multi-object detection and tracking799
This work performs a comprehensive quantitative study on the effects of object detection accuracy to the overall MOT performance, using the new large-scale University at Albany DETection and tRACking (UA-DETRAC) benchmark dataset.
- The Visual Object Tracking VOT2016 Challenge Results776
The Visual Object Tracking challenge VOT2016 goes beyond its predecessors by introducing a new semi-automatic ground truth bounding box annotation methodology and extending the evaluation system with the no-reset experiment.
- Invisible Backdoor Attack with Sample-Specific Triggers721
Inspired by the recent advance in DNN-based image steganography, sample-specific invisible additive noises as backdoor triggers are generated by encoding an attacker-specified string into benign images through an encoder-decoder network.
- 641
- Detecting Hidden Messages Using Higher-Order Statistics and Support Vector Machines570
An approach to detecting hidden messages in images that uses a wavelet-like decomposition to build higher-order statistical models of natural images and support vector machines are used to discriminate between untouched and adulterated images.
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- Object-Driven Text-To-Image Synthesis via Adversarial Training326
A thorough comparison between the classic grid attention and the new object-driven attention is provided through analyzing their mechanisms and visualizing their attention layers, showing insights of how the proposed model generates complex scenes in high quality.
- Multi-Scale Structure-Aware Network for Human Pose Estimation300
A robust multi-scale structure-aware neural network for human pose estimation that effectively improves state-of-the-art pose estimation methods that suffer from difficulties in scale varieties, occlusions, and complex multi-person scenarios.
- 279
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- Transcending Forgery Specificity with Latent Space Augmentation for Generalizable Deepfake Detection237
This work proposes a simple yet effective detector called LSDA (Latent Space Data Augmentation), based on a heuristic idea: representations with a wider variety of forgeries should be able to learn a more generalizable decision boundary, thereby mitigating the overfitting of method-specific features.
- Exposing Region Splicing Forgeries with Blind Local Noise Estimation230
An effective method to expose region splicing by revealing inconsistencies in local noise levels, based on the fact that images of different origins may have different noise characteristics introduced by the sensors or post-processing steps.
- Deepfake Detection: Current Challenges and Next Steps223
This paper highlights a few of challenges of high quality fake videos and audios generated by AI- algorithms (the deep fakes) and discusses the research opportunities in this direction.
- Stochastic online AUC maximization223
It is shown that AUC optimization can be equivalently formulated as a convex-concave saddle point problem and a stochastic online algorithm (SOLAM) is proposed which has time and space complexity of one datum.
- Celeb-DF: A New Dataset for DeepFake Forensics214
A new DeepFake dataset is presented, Celeb-DF, for the development and evaluation of DeepFake detection algorithms, generated using a refined synthesis algorithm that reduces the visual artifacts observed in existing datasets.
- A digital technique for art authentication212
A computational technique for authenticating works of art, specifically paintings and drawings, from high-resolution digital scans of the original works, is described, which confirms expert authentications of Pieter Bruegel the Elder.
- Steganalysis using color wavelet statistics and one-class support vector machines202
This paper extends statistical models using first-and higher-order wavelet statistics, and employed a non-linear support vector machines (SVM) to detect steganographic messages to exploit color statistics.
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Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-13. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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