Human Pose Forecasting On Human36M

Metriken

Average MPJPE (mm) @ 1000 ms

Average MPJPE (mm) @ 400ms

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

Vergleichstabelle

Modellname	Average MPJPE (mm) @ 1000 ms	Average MPJPE (mm) @ 400ms
a-unified-masked-autoencoder-with-patchified	112.1	61.6
a-mixer-layer-is-worth-one-graph-convolution	108.6	56.7
accurate-and-diverse-sampling-of-sequences	-	-
diverse-human-motion-prediction-guided-by	-	-
generating-smooth-pose-sequences-for-diverse	-	-
multiscale-residual-learning-of-graph	81.95	56.41
motionmixer-mlp-based-3d-human-body-pose	111.0	59.3
a-generic-diffusion-based-approach-for-3d	-	-
eqmotion-equivariant-multi-agent-motion	106.9	55.0
msr-gcn-multi-scale-residual-graph	114.2	62.9
hp-gan-probabilistic-3d-human-motion	-	-
gcnext-towards-the-unity-of-graph	64.7	30.5
towards-accurate-human-motion-prediction-via	109.2	55.5
space-time-separable-graph-convolutional-1	117.0	65.8
action-agnostic-human-pose-forecasting	-	-
imitation-learning-for-human-pose-prediction	-	-
auxiliary-tasks-benefit-3d-skeleton-based	107	54.1
the-pose-knows-video-forecasting-by	-	-
pages-iai-uni-bonn-de-https-pages-iai-uni	149.2	80.8
mt-vae-learning-motion-transformations-to	-	-
multi-graph-convolution-network-for-pose	72.9	34.4
anypose-anytime-3d-human-pose-forecasting-via	128.2	80.6
back-to-mlp-a-simple-baseline-for-human	109.4	57.3
remembering-what-is-important-a-factorised	-	34.8
deep-unsupervised-clustering-with-gaussian	-	-
structural-rnn-deep-learning-on-spatio	-	-
transfusion-a-practical-and-effective	-	-
learning-trajectory-dependencies-for-human	113.0	63.5
diverse-trajectory-forecasting-with	-	-
recurrent-network-models-for-human-dynamics	-	-
belfusion-latent-diffusion-for-behavior	-	-
progressively-generating-better-initial	110.3	58.5
diverse-human-motion-prediction-via-gumbel	-	-