git clone https://github.com/jonbarron/robust_loss_pytorch cd robust_loss_pytorch/ pip install -e .[dev] Tests can then be run from the root of the project using: nosetests Usage To use this code importlossfun, orAdaptiveLossFunctionand call the loss function.general.pyimplements the "gen...
Partially View-aligned Representation Learning with Noise-robust Contrastive Loss Requirements pytorch==1.5.0 numpy>=1.18.2 scikit-learn>=0.22.2 munkres>=1.1.2 logging>=0.5.1.2 Configuration The hyper-parameters, the training options (including the ratiao of positive to negative, aligned proportions...
This repository provides the official PyTorch implementation for the paper “Misalignment-Robust Frequency Distribution Loss for Image Transformation”, CVPR-2024. Paper About FDL This paper aims to address a common challenge in deep learning-based image transformation methods, such as image enhancement ...
Train Faster and Boost Performance with Class Hierarchies. Build Robust Representations Less Prone to Serious Classification Errors. - PyTorch code for paper: "A Hierarchical Loss for Semantic Segmentation" VISAPP/VISIGRAPP 2020 - brucemuller/Hierarchica
Code of TIP2021 Paper《SFace: Sigmoid-Constrained Hypersphere Loss for Robust Face Recognition》. We provide bothMxNet,PyTorchandJittorversions. Abstract Deep face recognition has achieved great success due to large-scale training databases and rapidly developing loss functions. The existing algorithms ...