Apr 28, 2020 · The dense supervision (DS-Res64) significantly improves the verification accuracy and the identification rate at low false accept rate, from ...
Apr 28, 2020 · We propose a novel training strategy to enhance the discriminability of deeply learned feature from another perspective, namely learning with dense supervision.
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Is face recognition supervised learning?
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What is heterogeneous face recognition?
The main idea is to apply multiple classification losses on top of multiple component features extracted from a single network. Ideally, each component feature ...
Our uniform method is able to achieve competitive results in various face analysis applications, such as occlusion detection, face recognition, gender ...
Sep 13, 2024 · This paper proposes a face detection model named Deep and Compact Face Detection (DCFD), which adopts an improved lightweight EfficientNetV2 network.
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Jul 4, 2023 · Extra supervision probably only means that you use other supervisory signals, in addition to the existing ones, like the picture suggests.
In this paper, we present a novel, self-taught, discriminative facial feature analysis approach in the weakly supervised framework. Our method can find regions ...
Dec 19, 2016 · We propose to overcome the sparsity of supervision problem via synthetically generated images. Building on a state-of-the-art image generation engine.
May 2, 2019 · This paper presents a robust single-stage face detector, named RetinaFace, which performs pixel-wise face localisation on various scales of faces.
The classification and regression head are both indis- pensable components to build up a dense object detector, which are usually supervised by the same ...