brucemuller / HierarchicalLossesLinks
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
☆9Updated last year
Alternatives and similar repositories for HierarchicalLosses
Users that are interested in HierarchicalLosses are comparing it to the libraries listed below
Sorting:
- CoaT: Co-Scale Conv-Attentional Image Transformers☆16Updated 4 years ago
- t-vMF Similarity for Regularizing Intra-Class Feature Distribution☆21Updated 3 years ago
- Utilities for Deep Learning with PyTorch (models, losses, metrics etc.)☆14Updated 4 years ago
- Official code for the paper: "A Closer Look at Self-training for Zero-Label Semantic Segmentation" https://arxiv.org/abs/2104.11692☆25Updated 3 years ago
- Official implementation for "Minimax Active Learning" in PyTorch.☆9Updated 4 years ago
- ICLR 2021 (spotlight): Graph Convolution with Low-rank Learnable Local Filters☆15Updated 4 years ago
- Official code for our SIBGRAPI 2020 paper: "IDA: Improved Data Augmentation Applied to Salient Object Detection"☆14Updated 3 years ago
- Generalized Max Pooling☆17Updated 5 years ago
- Code for paper "Object landmark discovery through unsupervised adaptation"☆37Updated 5 years ago
- Code for Paper "Evidential Softmax for Sparse MultimodalDistributions in Deep Generative Models"☆11Updated 3 years ago
- ☆41Updated 4 years ago
- ☆28Updated 5 years ago
- Semi-supervised learning with Grad-CAM consistency regularization☆10Updated 3 years ago
- Implementation and Benchmark Splits to study Out-of-Distribution Generalization in Deep Metric Learning.☆23Updated 3 years ago
- Locally Enhanced Self-Attention: Rethinking Self-Attention as Local and Context Terms☆20Updated 3 years ago
- Unofficial PyTorch implementation of "Filter Response Normalization Layer: Eliminating Batch Dependence in the Training of Deep Neural Ne…☆22Updated 5 years ago
- ☆26Updated 4 years ago
- The implementation of paper ''Efficient Attention Network: Accelerate Attention by Searching Where to Plug''.☆20Updated last year
- Official Pytorch implementation of the paper: "Locally Shifted Attention With Early Global Integration"☆15Updated 3 years ago
- Official code for NeurIPS paper "Combinatorial Optimization for Panoptic Segmentation: A Fully Differentiable Approach".☆16Updated 2 years ago
- Pytorch implementation of Graph U-Nets (ICML19)☆10Updated 4 years ago
- Implementation of the research paper of Cam which is the alternative to the current SOTA☆28Updated 2 years ago
- A Study of Deep Perceptual Metrics for Image quality Assessment☆11Updated 3 years ago
- ☆13Updated 3 years ago
- Code for our ICAR 2019 paper "ANDA: A Novel Data Augmentation Technique Applied to Salient Object Detection"☆21Updated 2 years ago
- Self-Supervised Domain Adaptation with Consistency Training☆19Updated 4 years ago
- TF 2 implementation Learning to Resize Images for Computer Vision Tasks (https://arxiv.org/abs/2103.09950v1).☆53Updated 3 years ago
- ☆10Updated 3 years ago
- ☆45Updated 3 years ago
- CVPR workshop (DiffCVML) 2020☆14Updated 5 years ago