naraysa
Interests: Weakly-supervised learning, Zero- /Few-shot learning
Technology Innovation InstituteUAE
Pinned Repositories
BiAM
[ICCV 2021] Official Pytorch implementation for Discriminative Region-based Multi-Label Zero-Shot Learning SOTA results on NUS-WIDE and OpenImages
tfvaegan
[ECCV 2020] Official Pytorch implementation for "Latent Embedding Feedback and Discriminative Features for Zero-Shot Classification". SOTA results for ZSL and GZSL
3c-net
Weakly-supervised Action Localization
CMU-MultimodalDataSDK
MultimodalSDK provides tools to easily apply machine learning algorithms on well-known affective computing datasets such as CMU-MOSI, CMU-MOSI2, POM, and ICT-MMMO.
CMU-MultimodalDataSDK-1
MultimodalSDK provides tools to easily apply machine learning algorithms on well-known affective computing datasets such as CMU-MOSI, CMU-MOSI2, POM, and ICT-MMMO.
D2-Net
[ICCV 2021] Official PyTorch implementation for "D2-Net: Weakly-Supervised Action Localization via Discriminative Embeddings and Denoised Activations"
gzsl-od
Out-of-Distribution Detection for Generalized Zero-Shot Action Recognition
PyVideoResearch
A repositsory of common methods, datasets, and tasks for video research
tfvaegan
Official repository for "Latent Embedding Feedback and Discriminative Features for Zero-Shot Classification" (ECCV 2020)
warp-ctc
Fast parallel CTC.
naraysa's Repositories
naraysa/gzsl-od
Out-of-Distribution Detection for Generalized Zero-Shot Action Recognition
naraysa/3c-net
Weakly-supervised Action Localization
naraysa/D2-Net
[ICCV 2021] Official PyTorch implementation for "D2-Net: Weakly-Supervised Action Localization via Discriminative Embeddings and Denoised Activations"
naraysa/PyVideoResearch
A repositsory of common methods, datasets, and tasks for video research
naraysa/CMU-MultimodalDataSDK
MultimodalSDK provides tools to easily apply machine learning algorithms on well-known affective computing datasets such as CMU-MOSI, CMU-MOSI2, POM, and ICT-MMMO.
naraysa/CMU-MultimodalDataSDK-1
MultimodalSDK provides tools to easily apply machine learning algorithms on well-known affective computing datasets such as CMU-MOSI, CMU-MOSI2, POM, and ICT-MMMO.
naraysa/tfvaegan
Official repository for "Latent Embedding Feedback and Discriminative Features for Zero-Shot Classification" (ECCV 2020)
naraysa/warp-ctc
Fast parallel CTC.