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/DRNet

DRNet

Reported on 39 benchmarks across 11 tasks · 3 papers · 28 SOTA

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

Medical17 results

ECG ClassificationonVIPL-HR
MAE· uses extra data· 2022-06-12
4.18
SOTA
DRNet: Decomposition and Reconstruction Network for Remote Physiological Measurement arXiv:2206.05687
ECG ClassificationonVIPL-HR
RMSE· uses extra data· 2022-06-12
6.78
SOTA
DRNet: Decomposition and Reconstruction Network for Remote Physiological Measurement arXiv:2206.05687
ECG ClassificationonUBFC-rPPG
MAE· uses extra data· 2022-06-12
0.42
SOTA
DRNet: Decomposition and Reconstruction Network for Remote Physiological Measurement arXiv:2206.05687
ECG ClassificationonUBFC-rPPG
Pearson Correlation· uses extra data· 2022-06-12
0.998
SOTA
DRNet: Decomposition and Reconstruction Network for Remote Physiological Measurement arXiv:2206.05687
ECG ClassificationonUBFC-rPPG
RMSE· uses extra data· 2022-06-12
0.64
SOTA
DRNet: Decomposition and Reconstruction Network for Remote Physiological Measurement arXiv:2206.05687
Photoplethysmography (PPG)onVIPL-HR
MAE· uses extra data· 2022-06-12
4.18
SOTA
DRNet: Decomposition and Reconstruction Network for Remote Physiological Measurement arXiv:2206.05687
Photoplethysmography (PPG)onVIPL-HR
RMSE· uses extra data· 2022-06-12
6.78
SOTA
DRNet: Decomposition and Reconstruction Network for Remote Physiological Measurement arXiv:2206.05687
Photoplethysmography (PPG)onUBFC-rPPG
MAE· uses extra data· 2022-06-12
0.42
SOTA
DRNet: Decomposition and Reconstruction Network for Remote Physiological Measurement arXiv:2206.05687
Photoplethysmography (PPG)onUBFC-rPPG
Pearson Correlation· uses extra data· 2022-06-12
0.998
SOTA
DRNet: Decomposition and Reconstruction Network for Remote Physiological Measurement arXiv:2206.05687
Photoplethysmography (PPG)onUBFC-rPPG
RMSE· uses extra data· 2022-06-12
0.64
SOTA
DRNet: Decomposition and Reconstruction Network for Remote Physiological Measurement arXiv:2206.05687
Blood pressure estimationonVIPL-HR
MAE· uses extra data· 2022-06-12
4.18
SOTA
DRNet: Decomposition and Reconstruction Network for Remote Physiological Measurement arXiv:2206.05687
Blood pressure estimationonVIPL-HR
RMSE· uses extra data· 2022-06-12
6.78
SOTA
DRNet: Decomposition and Reconstruction Network for Remote Physiological Measurement arXiv:2206.05687
Blood pressure estimationonUBFC-rPPG
MAE· uses extra data· 2022-06-12
0.42
SOTA
DRNet: Decomposition and Reconstruction Network for Remote Physiological Measurement arXiv:2206.05687
Blood pressure estimationonUBFC-rPPG
Pearson Correlation· uses extra data· 2022-06-12
0.998
SOTA
DRNet: Decomposition and Reconstruction Network for Remote Physiological Measurement arXiv:2206.05687
Blood pressure estimationonUBFC-rPPG
RMSE· uses extra data· 2022-06-12
0.64
SOTA
DRNet: Decomposition and Reconstruction Network for Remote Physiological Measurement arXiv:2206.05687
Semantic SegmentationonShapeNet-Part
Class Average IoU· 2020-05-14
83.7
best: 87.7 (Feature Geometric Net (FG-Net))
Dense-Resolution Network for Point Cloud Classification and Segmentation arXiv:2005.06734
Semantic SegmentationonShapeNet-Part
Instance Average IoU· 2020-05-14
86.4
best: 89.1 (GeomGCNN)
Dense-Resolution Network for Point Cloud Classification and Segmentation arXiv:2005.06734

Methodology10 results

Electrocardiography (ECG)onVIPL-HR
MAE· uses extra data· 2022-06-12
4.18
SOTA
DRNet: Decomposition and Reconstruction Network for Remote Physiological Measurement arXiv:2206.05687
Electrocardiography (ECG)onVIPL-HR
RMSE· uses extra data· 2022-06-12
6.78
SOTA
DRNet: Decomposition and Reconstruction Network for Remote Physiological Measurement arXiv:2206.05687
Electrocardiography (ECG)onUBFC-rPPG
MAE· uses extra data· 2022-06-12
0.42
SOTA
DRNet: Decomposition and Reconstruction Network for Remote Physiological Measurement arXiv:2206.05687
Electrocardiography (ECG)onUBFC-rPPG
Pearson Correlation· uses extra data· 2022-06-12
0.998
SOTA
DRNet: Decomposition and Reconstruction Network for Remote Physiological Measurement arXiv:2206.05687
Electrocardiography (ECG)onUBFC-rPPG
RMSE· uses extra data· 2022-06-12
0.64
SOTA
DRNet: Decomposition and Reconstruction Network for Remote Physiological Measurement arXiv:2206.05687
Medical waveform analysisonVIPL-HR
MAE· uses extra data· 2022-06-12
4.18
SOTA
DRNet: Decomposition and Reconstruction Network for Remote Physiological Measurement arXiv:2206.05687
Medical waveform analysisonVIPL-HR
RMSE· uses extra data· 2022-06-12
6.78
SOTA
DRNet: Decomposition and Reconstruction Network for Remote Physiological Measurement arXiv:2206.05687
Medical waveform analysisonUBFC-rPPG
MAE· uses extra data· 2022-06-12
0.42
SOTA
DRNet: Decomposition and Reconstruction Network for Remote Physiological Measurement arXiv:2206.05687
Medical waveform analysisonUBFC-rPPG
Pearson Correlation· uses extra data· 2022-06-12
0.998
SOTA
DRNet: Decomposition and Reconstruction Network for Remote Physiological Measurement arXiv:2206.05687
Medical waveform analysisonUBFC-rPPG
RMSE· uses extra data· 2022-06-12
0.64
SOTA
DRNet: Decomposition and Reconstruction Network for Remote Physiological Measurement arXiv:2206.05687

Computer Vision10 results

Shape Representation Of 3D Point CloudsonScanObjectNN
Mean Accuracy· 2020-05-14
78
best: 93.8 (GPSFormer)
SOTA
Dense-Resolution Network for Point Cloud Classification and Segmentation arXiv:2005.06734
3D Point Cloud ClassificationonScanObjectNN
Mean Accuracy· 2020-05-14
78
best: 93.8 (GPSFormer)
SOTA
Dense-Resolution Network for Point Cloud Classification and Segmentation arXiv:2005.06734
3D Point Cloud ReconstructiononScanObjectNN
Mean Accuracy· 2020-05-14
78
best: 93.8 (GPSFormer)
SOTA
Dense-Resolution Network for Point Cloud Classification and Segmentation arXiv:2005.06734
Spatial Relation RecognitiononRel3D
Acc· 2020-12-03
73.25
best: 94.25 (Human)
Rel3D: A Minimally Contrastive Benchmark for Grounding Spatial Relations in 3D arXiv:2012.01634
Shape Representation Of 3D Point CloudsonScanObjectNN
Overall Accuracy· 2020-05-14
80.3
best: 97.2 (OmniVec2)
Dense-Resolution Network for Point Cloud Classification and Segmentation arXiv:2005.06734
Shape Representation Of 3D Point CloudsonModelNet40
Overall Accuracy· 2020-05-14
93.1
best: 95.3 (PointGST)
Dense-Resolution Network for Point Cloud Classification and Segmentation arXiv:2005.06734
3D Point Cloud ClassificationonScanObjectNN
Overall Accuracy· 2020-05-14
80.3
best: 97.2 (OmniVec2)
Dense-Resolution Network for Point Cloud Classification and Segmentation arXiv:2005.06734
3D Point Cloud ClassificationonModelNet40
Overall Accuracy· 2020-05-14
93.1
best: 95.3 (PointGST)
Dense-Resolution Network for Point Cloud Classification and Segmentation arXiv:2005.06734
3D Point Cloud ReconstructiononScanObjectNN
Overall Accuracy· 2020-05-14
80.3
best: 97.2 (OmniVec2)
Dense-Resolution Network for Point Cloud Classification and Segmentation arXiv:2005.06734
3D Point Cloud ReconstructiononModelNet40
Overall Accuracy· 2020-05-14
93.1
best: 95.3 (PointGST)
Dense-Resolution Network for Point Cloud Classification and Segmentation arXiv:2005.06734

Audio2 results

10-shot image generationonShapeNet-Part
Class Average IoU· 2020-05-14
83.7
best: 87.7 (Feature Geometric Net (FG-Net))
Dense-Resolution Network for Point Cloud Classification and Segmentation arXiv:2005.06734
10-shot image generationonShapeNet-Part
Instance Average IoU· 2020-05-14
86.4
best: 89.1 (GeomGCNN)
Dense-Resolution Network for Point Cloud Classification and Segmentation arXiv:2005.06734