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/Fusionformer (f=9)

Fusionformer (f=9)

Reported on 12 benchmarks across 4 tasks · 1 paper

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

Computer Vision6 results

3D Human Pose EstimationonMPI-INF-3DHP
AUC· 2022-10-08
70
best: 87.7 (TCPFormer (T=81))
(Fusionformer):Exploiting the Joint Motion Synergy with Fusion Network Based On Transformer for 3D Human Pose Estimation arXiv:2210.04006
3D Human Pose EstimationonMPI-INF-3DHP
MPJPE· 2022-10-08
28.2
best: 124.7 (VNect (Augm.))
(Fusionformer):Exploiting the Joint Motion Synergy with Fusion Network Based On Transformer for 3D Human Pose Estimation arXiv:2210.04006
3D Human Pose EstimationonMPI-INF-3DHP
PCK· 2022-10-08
97.9
best: 99.37 (LMT R152 384x384)
(Fusionformer):Exploiting the Joint Motion Synergy with Fusion Network Based On Transformer for 3D Human Pose Estimation arXiv:2210.04006
Pose EstimationonMPI-INF-3DHP
AUC· 2022-10-08
70
best: 87.7 (TCPFormer (T=81))
(Fusionformer):Exploiting the Joint Motion Synergy with Fusion Network Based On Transformer for 3D Human Pose Estimation arXiv:2210.04006
Pose EstimationonMPI-INF-3DHP
MPJPE· 2022-10-08
28.2
best: 124.7 (VNect (Augm.))
(Fusionformer):Exploiting the Joint Motion Synergy with Fusion Network Based On Transformer for 3D Human Pose Estimation arXiv:2210.04006
Pose EstimationonMPI-INF-3DHP
PCK· 2022-10-08
97.9
best: 99.37 (LMT R152 384x384)
(Fusionformer):Exploiting the Joint Motion Synergy with Fusion Network Based On Transformer for 3D Human Pose Estimation arXiv:2210.04006

Methodology3 results

3DonMPI-INF-3DHP
AUC· 2022-10-08
70
best: 87.7 (TCPFormer (T=81))
(Fusionformer):Exploiting the Joint Motion Synergy with Fusion Network Based On Transformer for 3D Human Pose Estimation arXiv:2210.04006
3DonMPI-INF-3DHP
MPJPE· 2022-10-08
28.2
best: 124.7 (VNect (Augm.))
(Fusionformer):Exploiting the Joint Motion Synergy with Fusion Network Based On Transformer for 3D Human Pose Estimation arXiv:2210.04006
3DonMPI-INF-3DHP
PCK· 2022-10-08
97.9
best: 99.37 (LMT R152 384x384)
(Fusionformer):Exploiting the Joint Motion Synergy with Fusion Network Based On Transformer for 3D Human Pose Estimation arXiv:2210.04006

Audio3 results

1 Image, 2*2 StitchionMPI-INF-3DHP
AUC· 2022-10-08
70
best: 87.7 (TCPFormer (T=81))
(Fusionformer):Exploiting the Joint Motion Synergy with Fusion Network Based On Transformer for 3D Human Pose Estimation arXiv:2210.04006
1 Image, 2*2 StitchionMPI-INF-3DHP
MPJPE· 2022-10-08
28.2
best: 124.7 (VNect (Augm.))
(Fusionformer):Exploiting the Joint Motion Synergy with Fusion Network Based On Transformer for 3D Human Pose Estimation arXiv:2210.04006
1 Image, 2*2 StitchionMPI-INF-3DHP
PCK· 2022-10-08
97.9
best: 99.37 (LMT R152 384x384)
(Fusionformer):Exploiting the Joint Motion Synergy with Fusion Network Based On Transformer for 3D Human Pose Estimation arXiv:2210.04006