Tasks SotA Datasets Papers Methods Submit About

Papers With Code 2

A community resource for machine learning research: papers, code, benchmarks, and state-of-the-art results.

Explore

Notable Benchmarks All SotA Datasets Papers Methods

Community

Submit Results About

Data sourced from the PWC Archive (CC-BY-SA 4.0). Built by the community, for the community.

Models/SDR

SDR

Reported on 17 benchmarks across 6 tasks · 1 paper · 11 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Methodology12 results

Continual LearningonPASCAL VOC 2012
Mean IoU (val)· 2021-03-10
70.1
best: 82.6 (MBS)
SOTA
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations arXiv:2103.06342
Continual LearningonPASCAL VOC 2012
Mean IoU· 2021-03-10
67.3
best: 79 (MBS)
SOTA
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations arXiv:2103.06342
Class Incremental LearningonPASCAL VOC 2012
Mean IoU (val)· 2021-03-10
70.1
best: 82.6 (MBS)
SOTA
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations arXiv:2103.06342
Class Incremental LearningonPASCAL VOC 2012
Mean IoU· 2021-03-10
67.3
best: 79 (MBS)
SOTA
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations arXiv:2103.06342
Continual LearningonPASCAL VOC 2012
mIoU· 2021-03-10
25.1
best: 80.6 (MBS)
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations arXiv:2103.06342
Continual LearningonPASCAL VOC 2012
mIoU· 2021-03-10
39.5
best: 80.6 (MBS)
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations arXiv:2103.06342
Continual LearningonPASCAL VOC 2012
mIoU· 2021-03-10
48.7
best: 80.6 (MBS)
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations arXiv:2103.06342
Continual LearningonPASCAL VOC 2012
mIoU· 2021-03-10
14.3
best: 80.6 (MBS)
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations arXiv:2103.06342
Class Incremental LearningonPASCAL VOC 2012
mIoU· 2021-03-10
25.1
best: 80.6 (MBS)
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations arXiv:2103.06342
Class Incremental LearningonPASCAL VOC 2012
mIoU· 2021-03-10
39.5
best: 80.6 (MBS)
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations arXiv:2103.06342
Class Incremental LearningonPASCAL VOC 2012
mIoU· 2021-03-10
48.7
best: 80.6 (MBS)
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations arXiv:2103.06342
Class Incremental LearningonPASCAL VOC 2012
mIoU· 2021-03-10
14.3
best: 80.6 (MBS)
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations arXiv:2103.06342

Audio10 results

2D Semantic SegmentationonPASCAL VOC 2012
Mean IoU· 2021-03-10
67.3
best: 79 (MBS)
SOTA
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations arXiv:2103.06342
10-shot image generationonPASCAL VOC 2012
Mean IoU (val)· 2021-03-10
70.1
best: 82.6 (MBS)
SOTA
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations arXiv:2103.06342
10-shot image generationonPASCAL VOC 2012
Mean IoU· 2021-03-10
67.3
best: 79 (MBS)
SOTA
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations arXiv:2103.06342
2D Semantic SegmentationonPASCAL VOC 2012
mIoU· 2021-03-10
39.5
best: 80.6 (MBS)
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations arXiv:2103.06342
2D Semantic SegmentationonPASCAL VOC 2012
mIoU· 2021-03-10
48.7
best: 80.6 (MBS)
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations arXiv:2103.06342
2D Semantic SegmentationonPASCAL VOC 2012
mIoU· 2021-03-10
14.3
best: 80.6 (MBS)
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations arXiv:2103.06342
10-shot image generationonPASCAL VOC 2012
mIoU· 2021-03-10
25.1
best: 80.6 (MBS)
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations arXiv:2103.06342
10-shot image generationonPASCAL VOC 2012
mIoU· 2021-03-10
39.5
best: 80.6 (MBS)
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations arXiv:2103.06342
10-shot image generationonPASCAL VOC 2012
mIoU· 2021-03-10
48.7
best: 80.6 (MBS)
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations arXiv:2103.06342
10-shot image generationonPASCAL VOC 2012
mIoU· 2021-03-10
14.3
best: 80.6 (MBS)
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations arXiv:2103.06342

Medical6 results

Semantic SegmentationonPASCAL VOC 2012
Mean IoU (val)· 2021-03-10
70.1
best: 82.6 (MBS)
SOTA
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations arXiv:2103.06342
Semantic SegmentationonPASCAL VOC 2012
Mean IoU· 2021-03-10
67.3
best: 79 (MBS)
SOTA
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations arXiv:2103.06342
Semantic SegmentationonPASCAL VOC 2012
mIoU· 2021-03-10
25.1
best: 80.6 (MBS)
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations arXiv:2103.06342
Semantic SegmentationonPASCAL VOC 2012
mIoU· 2021-03-10
39.5
best: 80.6 (MBS)
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations arXiv:2103.06342
Semantic SegmentationonPASCAL VOC 2012
mIoU· 2021-03-10
48.7
best: 80.6 (MBS)
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations arXiv:2103.06342
Semantic SegmentationonPASCAL VOC 2012
mIoU· 2021-03-10
14.3
best: 80.6 (MBS)
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations arXiv:2103.06342

Computer Vision6 results

Class-Incremental Semantic SegmentationonPASCAL VOC 2012
Mean IoU (val)· 2021-03-10
70.1
best: 82.6 (MBS)
SOTA
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations arXiv:2103.06342
Class-Incremental Semantic SegmentationonPASCAL VOC 2012
Mean IoU· 2021-03-10
67.3
best: 79 (MBS)
SOTA
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations arXiv:2103.06342
Class-Incremental Semantic SegmentationonPASCAL VOC 2012
mIoU· 2021-03-10
25.1
best: 80.6 (MBS)
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations arXiv:2103.06342
Class-Incremental Semantic SegmentationonPASCAL VOC 2012
mIoU· 2021-03-10
39.5
best: 80.6 (MBS)
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations arXiv:2103.06342
Class-Incremental Semantic SegmentationonPASCAL VOC 2012
mIoU· 2021-03-10
48.7
best: 80.6 (MBS)
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations arXiv:2103.06342
Class-Incremental Semantic SegmentationonPASCAL VOC 2012
mIoU· 2021-03-10
14.3
best: 80.6 (MBS)
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations arXiv:2103.06342