Search Results for author:
Found 16 papers, 1 papers with code
Over-parameterization and Adversarial Robustness in Neural Networks: An Overview and Empirical Analysis
Relevant literature has claimed contradictory remarks in support of and against the robustness of over-parameterized networks.
Facial Kinship Verification from remote photoplethysmography
Specifically, in this paper, we employed a straightforward one-dimensional Convolutional Neural Network (1DCNN) with a 1DCNN-Attention module and kinship contrastive loss to learn the kin similarity from rPPGs.
Hardening RGB-D Object Recognition Systems against Adversarial Patch Attacks
We empirically show that this defense improves the performances of RGB-D systems against adversarial examples even when they are computed ad-hoc to circumvent this detection mechanism, and that is also more effective than adversarial training.
Why Adversarial Reprogramming Works, When It Fails, and How to Tell the Difference
Adversarial reprogramming allows repurposing a machine-learning model to perform a different task.
Non-contact Pain Recognition from Video Sequences with Remote Physiological Measurements Prediction
The framework is able to capture both local and long-range dependencies via the proposed attention mechanism for the learned appearance representations, which are further enriched by temporally attended physiological cues (remote photoplethysmography, rPPG) that are recovered from videos in the auxiliary task.
Are spoofs from latent fingerprints a real threat for the best state-of-art liveness detectors?
We investigated the threat level of realistic attacks using latent fingerprints against sensors equipped with state-of-art liveness detectors and fingerprint verification systems which integrate such liveness algorithms.
Revealing the Invisible with Model and Data Shrinking for Composite-database Micro-expression Recognition
In this paper, we analyze the influence of learning complexity, including the input complexity and model complexity, and discover that the lower-resolution input data and shallower-architecture model are helpful to ease the degradation of deep models in composite-database task.
Micro Expression Recognition
Micro-Expression Recognition
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Deep Neural Rejection against Adversarial Examples
Despite the impressive performances reported by deep neural networks in different application domains, they remain largely vulnerable to adversarial examples, i. e., input samples that are carefully perturbed to cause misclassification at test time.
Audio-Visual Kinship Verification
Then, early and late fusion methods are evaluated on the TALKIN dataset for the study of kinship verification with both face and voice modalities.
3D Face Mask Presentation Attack Detection Based on Intrinsic Image Analysis
So, we propose a novel detection method for 3D face mask presentation attack by modeling reflectance differences based on intrinsic image analysis.
Spatiotemporal Recurrent Convolutional Networks for Recognizing Spontaneous Micro-expressions
To exploit the merits of deep learning, we propose a novel deep recurrent convolutional networks based micro-expression recognition approach, capturing the spatial-temporal deformations of micro-expression sequence.
Face Presentation Attack Detection in Learned Color-liked Space
Face presentation attack detection (PAD) has become a thorny problem for biometric systems and numerous countermeasures have been proposed to address it.
Face Presentation Attack Detection
Generative Adversarial Network
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Kinship Verification from Videos using Spatio-Temporal Texture Features and Deep Learning
Automatic kinship verification using facial images is a relatively new and challenging research problem in computer vision.
Spontaneous Facial Micro-Expression Recognition using Discriminative Spatiotemporal Local Binary Pattern with an Improved Integral Projection
For increasing the discrimination of micro-expressions, we propose a new feature selection based on Laplacian method to extract the discriminative information for facial micro-expression recognition.
Local feature hierarchy for face recognition across pose and illumination
Accordingly we propose an end-to-end face recognition method to deal with pose and illumination simultaneously based on convolutional networks where the discriminative nonlinear features that are invariant to pose and illumination are extracted.
Unsupervised Deep Hashing for Large-scale Visual Search
Learning based hashing plays a pivotal role in large-scale visual search.
