Benchmarking Generalized Out-of-Distribution Detection
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Updated
Jul 14, 2024 - Python
Benchmarking Generalized Out-of-Distribution Detection
The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
[ICLR 2024 Spotlight] R-EDL: Relaxing Nonessential Settings of Evidential Deep Learning
A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques
Official code for CVPRW-2024 paper "ReweightOOD: Loss Reweighting for Distance-based OOD Detection".
Official code for CVPRW-2024 paper "T2FNorm: Train-time Feature Normalization for OOD Detection in Image Classification".
Out-of-distribution detection, robustness, and generalization resources. The repository contains a professionally curated list of papers, tutorials, books, videos, articles and open-source libraries etc
MUAD: Multiple Uncertainties for Autonomous Driving, a benchmark for multiple uncertainty types and tasks [BMVC 2022]
Python package to accelerate research on generalized out-of-distribution (OOD) detection.
Official code for paper "OpenCIL: Benchmarking Out-of-Distribution Detection in Class-Incremental Learning"
"A noisy elephant in the room: Is your out-of-distribution detector robust to label noise?" (CVPR 2024)
Official implementation for "Out-of-Distribution Detection in Long-Tailed Recognition with Calibrated Outlier Class Learning" (AAAI'24)
Official PyTorch code for "Out-of-distribution detection with denoising diffusion models"
Implementation of "Multiple Hypothesis Testing for Anomaly Detection in Multi-type Event Sequences" (ICDM 2023)
Code and Data Repo for Paper "Trajectory Volatility for Out-of-Distribution Detection in Mathematical Reasoning"
Fooling Machine Learning Models: A Novel Out-of-Distribution Attack through Generative Adversarial Networks
CSCI2470 Deep Learning Spring 2024: Enhancing Out-of-Distribution Object Detection with CLIP: A Vision-Language Approach
Simple, compact, and hackable post-hoc deep OOD detection for already trained tensorflow or pytorch image classifiers.
[ICCV'23 Oral] Unmasking Anomalies in Road-Scene Segmentation
NECO paper presented @ICLR2024
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