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/T2M-GPT (τ ∈ U[0, 1])

T2M-GPT (τ ∈ U[0, 1])

Reported on 16 benchmarks across 4 tasks · 1 paper · 4 SOTA

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

Audio8 results

10-shot image generationonKIT Motion-Language
R Precision Top3· 2023-01-15
0.745
best: 0.803 (BiPO)
SOTA
T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations arXiv:2301.06052
3D Human Pose TrackingonKIT Motion-Language
R Precision Top3· 2023-01-15
0.745
best: 0.803 (BiPO)
SOTA
T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations arXiv:2301.06052
10-shot image generationonKIT Motion-Language
Diversity· 2023-01-15
10.921
best: 11.198 (T2M-GPT (τ = 0))
T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations arXiv:2301.06052
10-shot image generationonKIT Motion-Language
FID· 2023-01-15
0.514
best: 0.131 (Motion Anything)
T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations arXiv:2301.06052
10-shot image generationonKIT Motion-Language
Multimodality· 2023-01-15
1.57
best: 3.627 (GraphMotion)
T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations arXiv:2301.06052
3D Human Pose TrackingonKIT Motion-Language
Diversity· 2023-01-15
10.921
best: 11.198 (T2M-GPT (τ = 0))
T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations arXiv:2301.06052
3D Human Pose TrackingonKIT Motion-Language
FID· 2023-01-15
0.514
best: 0.131 (Motion Anything)
T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations arXiv:2301.06052
3D Human Pose TrackingonKIT Motion-Language
Multimodality· 2023-01-15
1.57
best: 3.627 (GraphMotion)
T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations arXiv:2301.06052

Computer Vision4 results

Pose TrackingonKIT Motion-Language
R Precision Top3· 2023-01-15
0.745
best: 0.803 (BiPO)
SOTA
T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations arXiv:2301.06052
Pose TrackingonKIT Motion-Language
Diversity· 2023-01-15
10.921
best: 11.198 (T2M-GPT (τ = 0))
T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations arXiv:2301.06052
Pose TrackingonKIT Motion-Language
FID· 2023-01-15
0.514
best: 0.131 (Motion Anything)
T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations arXiv:2301.06052
Pose TrackingonKIT Motion-Language
Multimodality· 2023-01-15
1.57
best: 3.627 (GraphMotion)
T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations arXiv:2301.06052

Computer Code4 results

Motion SynthesisonKIT Motion-Language
R Precision Top3· 2023-01-15
0.745
best: 0.803 (BiPO)
SOTA
T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations arXiv:2301.06052
Motion SynthesisonKIT Motion-Language
Diversity· 2023-01-15
10.921
best: 11.198 (T2M-GPT (τ = 0))
T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations arXiv:2301.06052
Motion SynthesisonKIT Motion-Language
FID· 2023-01-15
0.514
best: 0.131 (Motion Anything)
T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations arXiv:2301.06052
Motion SynthesisonKIT Motion-Language
Multimodality· 2023-01-15
1.57
best: 3.627 (GraphMotion)
T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations arXiv:2301.06052