An awesome paper list of Semi-Supervised Learning under realistic settings.

Official PyTorch Repository of "Difficulty-Aware Simulator for Open Set Recognition" (ECCV 2022 Paper)

Interactive Skeleton Based Few Shot Action Recognition

Official Implementation of "Domain Adaptive Few-Shot Open-Set Learning" in IEEE/CVF International Conference on Computer Vision (ICCV'23)

Official code for paper "OpenCIL: Benchmarking Out-of-Distribution Detection in Class-Incremental Learning"

Building open-set image classification models via thresholding

OpenLoss: This repository discloses cost functions designed for open-set classification tasks, namely, Entropic Open-set, ObjectoSphere and Maximal-Entropy Loss.

Constructive categorial grammar supertagging with (pick any of: [heterogeneous | dynamic | attentive | structure-aware]) graph convolutions.

Accompanying code for the paper On Using Pre-Trained Embeddings for Detecting Anomalous Sounds with Limited Training Data.

Compact Implementation of Meta - Recognition and EVT Tools for Open-Set Classification

Maximal Entropy Loss

OpenLoss: This repository discloses cost functions designed for open-set classification tasks, namely, Entropic Open-set, ObjectoSphere and Maximal-Entropy Loss.

Implementation of CVPR'23 paper "Glocal Energy-based Learning for Few-Shot Open-Set Recognition"

Repository for the course Deep Learning Spring 2024

The primary objective of this project was to classify plant disease data, where the challenge was to identify not only known classes but also detect unknown classes during the testing phase.

Source code of PRJ paper "Learning Adversarial Semantic Embeddings for Zero-Shot Recognition in Open Worlds"