Zoo.md

April 9, 2021 · View on GitHub

This page presents model performance on H36M under various settings. Pre-trained models and instructions for reproduction can also be found.

Fully-supervised Setting (S15678)

Inference command:

python 2Dto3Dnet.py -evaluate True -twoD_source "HRN" -ckpt_dir "YourMODELPath"

Training command (Docs):

python 2Dto3Dnet.py -train True -num_stages 3 -num_blocks 3 -twoD_source "HRN" -evolved_path "YourDataPath"

Data synthesis command (Docs):

python evolve.py -SS "S15678" -T 1.5 -SD "YourDataPath" -generate True

MPJPE (P1) for each action under fully-supervised setting is shown in the table below.

Protocol #1	Dir.	Disc	Eat	Greet	Phone	Photo	Pose	Purch.	Sit	SitD.	Smoke	Wait	WalkD.	Walk	WalkT.	Avg.
Martinez et al. (ICCV'17)	51.8	56.2	58.1	59.0	69.5	78.4	55.2	58.1	74.0	94.6	62.3	59.1	65.1	49.5	52.4	62.9
Fang et al. (AAAI'18)	50.1	54.3	57.0	57.1	66.6	73.3	53.4	55.7	72.8	88.6	60.3	57.7	62.7	47.5	50.6	60.4
Yang et al. (CVPR'18)	51.5	58.9	50.4	57.0	62.1	65.4	49.8	52.7	69.2	85.2	57.4	58.4	43.6	60.1	47.7	58.6
Pavlakos et al. (CVPR'18)	48.5	54.4	54.4	52.0	59.4	65.3	49.9	52.9	65.8	71.1	56.6	52.9	60.9	44.7	47.8	56.2
Lee et al. (ECCV'18)	40.2	49.2	47.8	52.6	50.1	75.0	50.2	43.0	55.8	73.9	54.1	55.6	58.2	43.3	43.3	52.8
Zhao et al. (CVPR'19)	47.3	60.7	51.4	60.5	61.1	49.9	47.3	68.1	86.2	55.0	67.8	61.0	42.1	60.6	45.3	57.6
Sharma et al. (ICCV'19)	48.6	54.5	54.2	55.7	62.6	72.0	50.5	54.3	70.0	78.3	58.1	55.4	61.4	45.2	49.7	58.0
Moon et al. (ICCV'19)	51.5	56.8	51.2	52.2	55.2	47.7	50.9	63.3	69.9	54.2	57.4	50.4	42.5	57.5	47.7	54.4
Liu et al. (ECCV'20)	46.3	52.2	47.3	50.7	55.5	67.1	49.2	46.0	60.4	71.1	51.5	50.1	54.5	40.3	43.7	52.4
Ours (S15678)	45.6	44.6	49.3	49.3	52.5	58.5	46.4	44.3	53.8	67.5	49.4	46.1	52.5	41.4	44.4	49.7

MPJPE (P2) for each action under fully-supervised setting is shown in the table below.

Protocol #2	Dir.	Disc	Eat	Greet	Phone	Photo	Pose	Purch.	Sit	SitD.	Smoke	Wait	WalkD.	Walk	WalkT.	Avg.
Martinez et al. (ICCV'17)	39.5	43.2	46.4	47.0	51.0	56.0	41.4	40.6	56.5	69.4	49.2	45.0	49.5	38.0	43.1	47.7
Fang et al. (AAAI'18)	38.2	41.7	43.7	44.9	48.5	55.3	40.2	38.2	54.5	64.4	47.2	44.3	47.3	36.7	41.7	45.7
Pavlakos et al. (CVPR'18)	34.7	39.8	41.8	38.6	42.5	47.5	38.0	36.6	50.7	56.8	42.6	39.6	43.9	32.1	36.5	41.8
Yang et al. (CVPR'18)	26.9	30.9	36.3	39.9	43.9	47.4	28.8	29.4	36.9	58.4	41.5	30.5	29.5	42.5	32.2	37.7
Sharma et al. (ICCV'19)	35.3	35.9	45.8	42.0	40.9	52.6	36.9	35.8	43.5	51.9	44.3	38.8	45.5	29.4	34.3	40.9
Cai et al. (ICCV'19)	35.7	37.8	36.9	40.7	39.6	45.2	37.4	34.5	46.9	50.1	40.5	36.1	41.0	29.6	33.2	39.0
Liu et al. (ECCV'20)	35.9	40.0	38.0	41.5	42.5	51.4	37.8	36.0	48.6	56.6	41.8	38.3	42.7	31.7	36.2	41.2
Ours (S15678)	34.2	34.6	37.3	39.3	38.5	45.6	34.5	32.7	40.5	51.3	37.7	35.4	39.9	29.9	34.5	37.7

Inference command:

python 2Dto3Dnet.py -evaluate True -twoD_source "HRN" -ckpt_dir "YourMODELPath"

Training command (Docs):

python 2Dto3Dnet.py -train True -num_stages 2 -ws True -ws_name "S1" -twoD_source "HRN" -evolved_path "YourDataPath"

Data synthesis command (Docs):

python evolve.py -generate True -WS True -SS "S1"

MPJPE (P1) for each action under weakly-supervised setting is shown in the table below.

Protocol #1	Dir.	Disc	Eat	Greet	Phone	Photo	Pose	Purch.	Sit	SitD.	Smoke	Wait	WalkD.	Walk	WalkT.	Avg.
Kocabas et al. (CVPR'19)	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	65.3
Pavllo et al. (CVPR'19)	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	64.7
Li et al. (ICCV'19)	70.4	83.6	76.6	78.0	85.4	106.1	72.2	103.0	115.8	165.0	82.4	74.3	94.6	60.1	70.6	88.8
Ours (S1)	52.8	56.6	54.0	57.5	62.8	72.0	55.0	61.3	65.8	80.7	58.9	56.7	69.7	51.6	57.2	60.8

MPJPE (P2) for each action under fully-supervised setting is shown in the table below.

Protocol #2	Dir.	Disc	Eat	Greet	Phone	Photo	Pose	Purch.	Sit	SitD.	Smoke	Wait	WalkD.	Walk	WalkT.	Avg.
Rhodin et al. (CVPR'18)	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	64.6
Kocabas et al. (CVPR'19)	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	57.2
Li et al. (ICCV'19)	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	66.5
Ours (S1)	40.2	43.4	41.9	46.1	48.2	55.1	42.8	42.6	49.6	61.1	44.5	43.2	51.5	38.1	44.4	46.2