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We propose the adaptive robust loss, a unified loss function for both of the two landmark detection paradigms. The adaptive robust loss benefits them through adjusting the enhancement of small errors adaptively according to the ground-truth. We modify the MobileNet V2 as the multi-scale fusion network.
Jan 1, 2024 · In this paper, we propose a unified loss function called Adaptive Robust loss (ARobust loss) that is tailored for two landmark detection ...
This chapter proposes a novel loop closure detection framework for visual based navigation and mapping. The proposed approach eliminates the training stage and ...
Release pretrained model and code on 300W, AFLW and COFW dataset. Replease facial landmark detection API. Citation. If you find this useful for your research, ...
Robust facial landmark detection un- der significant head poses and occlusion. In Proceedings of the IEEE International Conference on Computer Vision, pages ...
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This total loss encourages the attacker to suitably perturb training data to produce adversarial examples that can im- prove the robustness of the detector ...
Jun 24, 2019 · This probabilistic interpretation enables the training of neural networks in which the robustness of the loss automatically adapts itself during ...
Missing: landmark | Show results with:landmark
Apr 16, 2019 · In this paper, we analyze the ideal loss function properties for heatmap regression in face alignment problems. Then we propose a novel loss ...
Missing: detection. | Show results with:detection.
This paper introduces "Adaloss", an objective function that adapts itself during the training by updating the target precision based on the training ...
Variational autoencoders [23, 31] are a landmark technique for training autoencoders as generative models, which can then be used to draw random samples that ...