UniMatch V2: Pushing the Limit of Semi-Supervised Semantic Segmentation | ✓ Link | 84.3% | UniMatch V2 (DINOv2-B) | 2024-10-14 |
SemiVL: Semi-Supervised Semantic Segmentation with Vision-Language Guidance | ✓ Link | 79.4% | SemiVL (ViT-B/16) | 2023-11-27 |
Revisiting and Maximizing Temporal Knowledge in Semi-supervised Semantic Segmentation | ✓ Link | 78.9% | PrevMatch (ResNet-101) | 2024-05-31 |
CorrMatch: Label Propagation via Correlation Matching for Semi-Supervised Semantic Segmentation | ✓ Link | 78.5% | CorrMatch (Deeplabv3+ with ResNet-101) | 2023-06-07 |
FARCLUSS: Fuzzy Adaptive Rebalancing and Contrastive Uncertainty Learning for Semi-Supervised Semantic Segmentation | ✓ Link | 78.5 | FARCLUSS | 2025-06-11 |
Switching Temporary Teachers for Semi-Supervised Semantic Segmentation | ✓ Link | 78.4 | Dual Teacher | 2023-09-21 |
Revisiting Weak-to-Strong Consistency in Semi-Supervised Semantic Segmentation | ✓ Link | 77.92% | UniMatch (DeepLab v3+ with ImageNet-pretrained ResNet-101, single scale inference) | 2022-08-21 |
Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning | ✓ Link | 77.9% | AEL (DeepLab v3+ with ResNet-101 pretraind on ImageNet-1K) | 2021-10-11 |
Revisiting and Maximizing Temporal Knowledge in Semi-supervised Semantic Segmentation | ✓ Link | 77.8% | PrevMatch (ResNet-50) | 2024-05-31 |
Semi-Supervised Semantic Segmentation via Marginal Contextual Information | ✓ Link | 77.78% | S4MC | 2023-08-26 |
Semi-Supervised Semantic Segmentation with Cross Pseudo Supervision | ✓ Link | 77.62% | CPS (DeepLab v3+ with ImageNet-pretrained ResNet-101, single scale inference) | 2021-06-02 |
n-CPS: Generalising Cross Pseudo Supervision to n Networks for Semi-Supervised Semantic Segmentation | | 77.61% | n-CPS (ResNet-50) | 2021-12-14 |
Confidence-Weighted Boundary-Aware Learning for Semi-Supervised Semantic Segmentation | ✓ Link | 77.20% | CW-BASS (DeepLab v3+ with ResNet-50) | 2025-02-21 |
Perturbed and Strict Mean Teachers for Semi-supervised Semantic Segmentation | ✓ Link | 77.12% | PS-MT (DeepLab v3+ with ImageNet-pretrained ResNet50, single scale inference) | 2021-11-25 |
LaserMix for Semi-Supervised LiDAR Semantic Segmentation | ✓ Link | 77.1% | LaserMix (DeepLab v3+, ImageNet pre-trained ResNet50, single scale inference) | 2022-06-30 |
Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels | ✓ Link | 76.48% | U2PL (DeepLab v3+ with ResNet-101 pretraind on ImageNet-1K, AEL) | 2022-03-08 |
Semi-supervised Semantic Segmentation with Prototype-based Consistency Regularization | ✓ Link | 76.31% | PCR (DeepLab v3+ with ResNet-101 pretraind on ImageNet-1K) | 2022-10-10 |
Conservative-Progressive Collaborative Learning for Semi-supervised Semantic Segmentation | ✓ Link | 74.6% | CPCL (DeepLab v3+ with ResNet-50) | 2022-11-30 |
A Simple Baseline for Semi-supervised Semantic Segmentation with Strong Data Augmentation | ✓ Link | 74.1% | SimpleBaseline(DeeplabV3+ with ImageNet pretrained Xception65, sinle scale inference) | 2021-04-15 |
Dense FixMatch: a simple semi-supervised learning method for pixel-wise prediction tasks | ✓ Link | 73.91% | Dense FixMatch (DeepLabv3+ ResNet-101, uniform sampling, single pass eval) | 2022-10-18 |
Dense FixMatch: a simple semi-supervised learning method for pixel-wise prediction tasks | ✓ Link | 73.39% | Dense FixMatch (DeepLabv3+ ResNet-50, uniform sampling, single pass eval) | 2022-10-18 |
Semi-supervised Semantic Segmentation with Error Localization Network | ✓ Link | 70.33% | Error Localization Network (DeeplabV3 with ResNet-50) | 2022-04-05 |
Three Ways to Improve Semantic Segmentation with Self-Supervised Depth Estimation | ✓ Link | 68.01% | SegSDE (MTL decoder with ResNet101, ImageNet pretrained, unlabeled image sequences) | 2020-12-19 |
Bootstrapping Semantic Segmentation with Regional Contrast | ✓ Link | 66.44% | ReCo (DeepLab v3+ with ResNet-101 backbone, ImageNet pretrained) | 2021-04-09 |
GuidedMix-Net: Learning to Improve Pseudo Masks Using Labeled Images as Reference | ✓ Link | 65.8% | GuidedMix-Net(DeepLab v2 with ResNet101, ImageNet pretrained) | 2021-06-29 |
Bootstrapping Semantic Segmentation with Regional Contrast | ✓ Link | 64.94% | ReCo (DeepLab v2 with ResNet-101 backbone, ImageNet pretrained) | 2021-04-09 |
Semi-Supervised Semantic Segmentation with Pixel-Level Contrastive Learning from a Class-wise Memory Bank | ✓ Link | 64.4% | SemiSegContrast
(DeepLab v2 with ResNet-101 backbone, MSCOCO pretrained) | 2021-04-27 |
DMT: Dynamic Mutual Training for Semi-Supervised Learning | ✓ Link | 63.03% | DMT (DeepLab v2 MSCOCO/ImageNet pre-trained) | 2020-04-18 |
The GIST and RIST of Iterative Self-Training for Semi-Supervised Segmentation | | 62.57% | GIST and RIST (DeepLabv2 with ResNet101, MSCOCO pre-trained) | 2021-03-31 |
ClassMix: Segmentation-Based Data Augmentation for Semi-Supervised Learning | ✓ Link | 61.35% | ClassMix (DeepLab v2 MSCOCO pretrained) | 2020-07-15 |
Semi-supervised semantic segmentation needs strong, varied perturbations | ✓ Link | 60.34% | CutMix (DeepLab v2, ImageNet pre-trained) | 2019-06-05 |
Semi-Supervised Semantic Segmentation with High- and Low-level Consistency | ✓ Link | 59.3% | s4GAN (DeepLab v2 ImageNet pre-trained) | 2019-08-15 |
Adversarial Learning for Semi-Supervised Semantic Segmentation | ✓ Link | 57.1% | Adversarial (DeepLab v2 ImageNet pre-trained) | 2018-02-22 |