Bachelor's thesis work on Uncertainty in neural network classifiers
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Updated
Jun 1, 2021 - Python
Bachelor's thesis work on Uncertainty in neural network classifiers
OpenLoss: This repository discloses cost functions designed for open-set classification tasks, namely, Entropic Open-set, ObjectoSphere and Maximal-Entropy Loss.
Open-Set Support Vector Machines (OSSVM) [see commit message https://github.com/pedrormjunior/ossvm/commit/50d51dc482c8e13df7d9037976b97db7e60a1ccf for usage]
Open-Set Domain Adaptation through Self-Supervision, using a ROS task this repository contains the python implementation of the final project for the course of Data Analysis & Artificial Intelligence
[CVPR 2022 Oral] Towards Open Set Temporal Action Localization
Efficient and User-Friendly Time Series Analysis Library for PyOpenTS with pytorch compatibility.
Interactive Skeleton Based Few Shot Action Recognition
Open-Set Recognition Using Intra-Class Splitting
A project to train your model from scratch or fine-tune a pretrained model using the losses provided in this library to improve out-of-distribution detection and uncertainty estimation performances. Calibrate your model to produce enhanced uncertainty estimations. Detect out-of-distribution data using the defined score type and threshold.
Code release for Mind the Gap: Enlarging the Domain Gap in Open Set Domain Adaptation (TCSVT 2023)
A project to improve out-of-distribution detection (open set recognition) and uncertainty estimation by changing a few lines of code in your project! Perform efficient inferences (i.e., do not increase inference time) without repetitive model training, hyperparameter tuning, or collecting additional data.
Paper: Towards Open-Set Face Recognition using Hashing Functions (IJCB'17)
Tensorflow Implementation on Paper [AAAI2020]Semi-Supervised Learning under Class Distribution Mismatch
[CVPR 2021] Exemplar-Based Open-Set Panoptic Segmentation Network (EOPSN)
A project to add scalable state-of-the-art out-of-distribution detection (open set recognition) support by changing two lines of code! Perform efficient inferences (i.e., do not increase inference time) and detection without classification accuracy drop, hyperparameter tuning, or collecting additional data.
API for Grounding DINO 1.5: IDEA Research's Most Capable Open-World Object Detection Model Series
Open Set Recognition
Code and data for the research paper "Towards Open Set Deep Networks" A Bendale, T Boult, CVPR 2016
API for T-Rex2: Towards Generic Object Detection via Text-Visual Prompt Synergy
Pytorch implementation for "Large-Scale Long-Tailed Recognition in an Open World" (CVPR 2019 ORAL)
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