Exploiting temporal and depth information for multi-frame face anti-spoofing

Abstract

Face anti-spoofing is significant to the security of face recognition systems. Previous works on depth supervised learning have proved the effectiveness for face anti-spoofing. Nevertheless, they only considered the depth as an auxiliary supervision in the single frame. Different from these methods, we develop a new method to estimate depth information from multiple RGB frames and propose a depth-supervised architecture which can efficiently encodes spatiotemporal information for presentation attack detection. It includes two novel modules: optical flow guided feature block (OFFB) and convolution gated recurrent units (ConvGRU) module, which are designed to extract short-term and long-term motion to discriminate living and spoofing faces. Extensive experiments demonstrate that the proposed approach achieves state-of-the-art results on four benchmark datasets, namely OULU-NPU, SiW, CASIA-MFSD, and Replay-Attack.

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Cited by in corpus (18)

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• CelebA-Spoof: Large-Scale Face Anti-Spoofing Dataset with Rich Annotations
• A Dataset and Benchmark for Large-scale Multi-modal Face Anti-spoofing
• CASIA-SURF: A Large-scale Multi-modal Benchmark for Face Anti-spoofing
• Face Anti-Spoofing Via Disentangled Representation Learning
• Deep Frequent Spatial Temporal Learning for Face Anti-Spoofing
• Static and Dynamic Fusion for Multi-modal Cross-ethnicity Face Anti-spoofing
• A Survey On Anti-Spoofing Methods For Face Recognition with RGB Cameras of Generic Consumer Devices
• FeatherNets: Convolutional Neural Networks as Light as Feather for Face Anti-spoofing
• CASIA-SURF CeFA: A Benchmark for Multi-modal Cross-ethnicity Face Anti-spoofing
• Improving Face Anti-Spoofing by 3D Virtual Synthesis
• Style Transfer Applied to Face Liveness Detection with User-Centered Models
• Two-stream Convolutional Networks for Multi-frame Face Anti-spoofing
• Uncertainty-Aware Physically-Guided Proxy Tasks for Unseen Domain Face Anti-spoofing
• Multi-Frames Temporal Abnormal Clues Learning Method for Face Anti-Spoofing
• Face Anti-Spoofing with Human Material Perception