PyTorch Implementation for Deep Metric Learning Pipelines
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Updated
Jun 17, 2020 - Python
PyTorch Implementation for Deep Metric Learning Pipelines
Comparison of famous convolutional neural network models
Fine grained visual recognition tensorflow baseline on CUB, Stanford Cars, Dogs, Aircrafts, and Flower102.
Hardness-Aware Deep Metric Learning (CVPR2019) in pytorch
(ICCV 2019) This repo contains code for "MIC: Mining Interclass Characteristics for Improved Metric Learning", which proposes an auxiliary training task to explain away intra-class variations.
Explores jigsaw puzzles solvinig as pre-text task for fine grained classification for bird species identification (Implemented with pyTorch)
Replication of DeCAF paper's experiments for transfer learning
PartCraft: Crafting Creative Objects by Parts (ECCV2024)
pytorch STN implement for CUB200 dataset
Research for text-to-image synthesis via modified auxiliary classifier GANs. Incremental modification of model architecture for improved results, fully documented.
PyTorch implementation for "Gated Transfer Network for Transfer Learning"
A study on the interpretability of the concepts learned by Prototypical Part Networks (ProtoPNets) on the CUB200-2011 and CelebAMask datasets.
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