Lists (1)
Stars
This is the dataset which has lots of shadow crack images and corresponding binary ground truth maps.
[arXiv] The official code for "UltraLight VM-UNet: Parallel Vision Mamba Significantly Reduces Parameters for Skin Lesion Segmentation".
Official code for Class Tokens Infusion for Weakly Supervised Semantic Segmentation, CVPR2024
Code for "From classification to segmentation with explainable AI: A study on crack detection and growth monitoring" (Automation in Construction 2024)
A Pytorch implementation of Generative Adversarial Network for Heuristics of Sampling-based Path Planning
Code used to obtain the results presented in the paper
A collection of resources and papers on Diffusion Models
[CVPR'23] Augmentation Matters: A Simple-yet-Effective Approach to Semi-supervised Semantic Segmentation
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
Adversarial Erasing Framework via Triplet with Gated Pyramid Pooling Layer for Weakly Supervised Semantic Segmentation, ECCV2022
Weakly Supervised Learning of Instance Segmentation with Inter-pixel Relations, CVPR 2019 (Oral)
Learning Pixel-level Semantic Affinity with Image-level Supervision for Weakly Supervised Semantic Segmentation, CVPR 2018
Weakly-Supervised-Learning, Semantic Segmentation, CVPR 2023
Pseudo-mask Matters in Weakly-supervised Semantic Segmentation
Unlocking the Potential of Ordinary Classifier: Class-specific Adversarial Erasing Framework for Weakly Supervised Semantic Segmentation, ICCV 2021
Official repository for CVPR 2023 paper: WSSS via Adversarial Learning of Classifier and Reconstructor
Quickly comparing your image classification models with the state-of-the-art models (such as DenseNet, ResNet, ...)
Official code for ICIP 2023 paper "A Convolutional-Transformer Network for Crack Segmentation with Boundary Awareness"
Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything
Open-source and strong foundation image recognition models.
[CVPR 2022] ST++: Make Self-training Work Better for Semi-supervised Semantic Segmentation
[CVPR'22] Perturbed and Strict Mean Teachers for Semi-supervised Semantic Segmentation
Semi-supervised Semantic Segmentation with Directional Context-aware Consistency (CVPR 2021)