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Found 12 papers, 5 papers with code
Deep Learning Techniques for Video Instance Segmentation: A Survey
Video instance segmentation, also known as multi-object tracking and segmentation, is an emerging computer vision research area introduced in 2019, aiming at detecting, segmenting, and tracking instances in videos simultaneously.
S-Adapter: Generalizing Vision Transformer for Face Anti-Spoofing with Statistical Tokens
Face Anti-Spoofing (FAS) aims to detect malicious attempts to invade a face recognition system by presenting spoofed faces.
Hyperbolic Face Anti-Spoofing
To further improve generalization, we conduct hyperbolic contrastive learning for the bonafide only while relaxing the constraints on diverse spoofing attacks.
Beyond the Prior Forgery Knowledge: Mining Critical Clues for General Face Forgery Detection
Face forgery detection is essential in combating malicious digital face attacks.
Self-Supervised 3D Action Representation Learning with Skeleton Cloud Colorization
We investigate self-supervised representation learning and design a novel skeleton cloud colorization technique that is capable of learning spatial and temporal skeleton representations from unlabeled skeleton sequence data.
Rehearsal-Free Domain Continual Face Anti-Spoofing: Generalize More and Forget Less
To alleviate the forgetting of previous domains without using previous data, we propose the Proxy Prototype Contrastive Regularization (PPCR) to constrain the continual learning with previous domain knowledge from the proxy prototypes.
Rethinking Vision Transformer and Masked Autoencoder in Multimodal Face Anti-Spoofing
In this paper, we investigate three key factors (i. e., inputs, pre-training, and finetuning) in ViT for multimodal FAS with RGB, Infrared (IR), and Depth.
One-Class Knowledge Distillation for Face Presentation Attack Detection
Under this framework, a teacher network is trained with source domain samples to provide discriminative feature representations for face PAD.
Self-Supervised Leaf Segmentation under Complex Lighting Conditions
As an essential prerequisite task in image-based plant phenotyping, leaf segmentation has garnered increasing attention in recent years.
Asymmetric Modality Translation For Face Presentation Attack Detection
In this paper, we propose a novel framework based on asymmetric modality translation for face presentation attack detection in bi-modality scenarios.
Learning Meta Pattern for Face Anti-Spoofing
To improve the generalization ability, recent hybrid methods have been explored to extract task-aware handcrafted features (e. g., Local Binary Pattern) as discriminative information for the input of DNNs.
Variational Representation Learning for Vehicle Re-Identification
One of the most challenging problems is to learn an efficient representation for a vehicle from its multi-viewpoint images.
