zhouhuan-hust's repositories
LFD_RoadSeg
[IEEE TITS] Exploiting Low-level Representations for Ultra-Fast Road Segmentation
anomaly-seg
The Combined Anomalous Object Segmentation (CAOS) Benchmark
DenseHybrid
Official implementation of paper "DenseHybrid: Hybrid Anomaly Detection for Dense Open-set Recognition"
detecting-the-unexpected
Detecting the Unexpected via Image Resynthesis
Entity
EntitySeg Toolbox: Towards Open-World and High-Quality Image Segmentation
ICCV21_SCOOD
The Official Implementation of the ICCV-2021 Paper: Semantically Coherent Out-of-Distribution Detection.
Open-World-Semantic-Segmentation
Code for ICCV2021 paper "Deep Metric Learning for Open World Semantic Segmentation".
PEBAL
[ECCV'22 Oral] Pixel-wise Energy-biased Abstention Learning for Anomaly Segmentation on Complex Urban Driving Scenes
pytorch-grad-cam
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
pytorch-loss
label-smooth, amsoftmax, partial-fc, focal-loss, triplet-loss, lovasz-softmax. Maybe useful
RepLKNet-pytorch
Scaling Up Your Kernels to 31x31: Revisiting Large Kernel Design in CNNs (CVPR 2022)
road-anomaly-benchmark
Benchmark of detection methods for anomalies and obstacles in traffic images.
SegFormer
Official PyTorch implementation of SegFormer
segmentation_models.pytorch
Segmentation models with pretrained backbones. PyTorch.
semseg
Semantic Segmentation in Pytorch
Standardized-max-logits
Official PyTorch implementation of paper: Standardized Max Logits: A Simple yet Effective Approach for Identifying Unexpected Road Obstacles in Urban-Scene Segmentation (ICCV 2021 Oral Presentation)
synboost
Paper implementation of SynBoost