From cba1d661cd8219e3dfbcdd1b1771c73caf70d595 Mon Sep 17 00:00:00 2001 From: Yufei Date: Tue, 24 May 2022 13:26:34 +0800 Subject: [PATCH] rename and add news --- README.md | 14 ++++++++------ 1 file changed, 8 insertions(+), 6 deletions(-) diff --git a/README.md b/README.md index 3df4599..2aff57d 100644 --- a/README.md +++ b/README.md @@ -19,7 +19,7 @@ This branch contains the pytorch implementation of ViTPose: Simple Vision Transformer Baselines for Human Pose Estimation. It obtains 81.1 AP on MS COCO Keypoint test-dev set. -## Results from this repo on MS COCO val set (single task training) +## Results from this repo on MS COCO val set (single-task training) Using detection results from a detector that obtains 56 mAP on person. The configs here are for both training and test. @@ -39,7 +39,7 @@ Using detection results from a detector that obtains 56 mAP on person. The confi | ViTPose-L | MAE | 256x192 | 78.2 | 83.4 | [config](configs/body/2d_kpt_sview_rgb_img/topdown_heatmap/coco/ViTPose_large_simple_coco_256x192.py) | [log](logs/vitpose-l-simple.log.json) | [Onedrive](https://1drv.ms/u/s!AimBgYV7JjTlgSVS6DP2LmKwZ3sm?e=MmCvDT) | | ViTPose-H | MAE | 256x192 | 78.9 | 84.0 | [config](configs/body/2d_kpt_sview_rgb_img/topdown_heatmap/coco/ViTPose_huge_simple_coco_256x192.py) | [log](logs/vitpose-h-simple.log.json) | [Onedrive](https://1drv.ms/u/s!AimBgYV7JjTlgSbHyN2mjh2n2LyG?e=y0FgMK) | -## Results from this repo on MS COCO val set (multi task training) +## Results from this repo on MS COCO val set (multi-task training) Using detection results from a detector that obtains 56 mAP on person. Note the configs here are only for evaluation. @@ -50,7 +50,7 @@ Using detection results from a detector that obtains 56 mAP on person. Note the | ViTPose-H | COCO+AIC+MPII+CrowdPose | 256x192 | 79.8 | 84.8 | [config](configs/body/2d_kpt_sview_rgb_img/topdown_heatmap/coco/ViTPose_huge_coco_256x192.py) | [Onedrive](https://1drv.ms/u/s!AimBgYV7JjTlgS5rLeRAJiWobCdh?e=41GsDd) | | ViTPose-G | COCO+AIC+MPII+CrowdPose | 576x432 | 81.0 | 85.6 | | | -## Results from this repo on OCHuman test set (multi task training) +## Results from this repo on OCHuman test set (multi-task training) Using groundtruth bounding boxes. Note the configs here are only for evaluation. @@ -61,7 +61,7 @@ Using groundtruth bounding boxes. Note the configs here are only for evaluation. | ViTPose-H | COCO+AIC+MPII+CrowdPose | 256x192 | 91.6 | 92.8 | [config](configs/body/2d_kpt_sview_rgb_img/topdown_heatmap/ochuman/ViTPose_huge_ochuman_256x192.py) | [Onedrive](https://1drv.ms/u/s!AimBgYV7JjTlgS5rLeRAJiWobCdh?e=41GsDd) | | ViTPose-G | COCO+AIC+MPII+CrowdPose | 576x432 | 93.3 | 94.3 | | | -## Results from this repo on CrowdPose test set (multi task training) +## Results from this repo on CrowdPose test set (multi-task training) Using YOLOv3 human detector. Note the configs here are only for evaluation. @@ -72,7 +72,7 @@ Using YOLOv3 human detector. Note the configs here are only for evaluation. | ViTPose-H | COCO+AIC+MPII+CrowdPose | 256x192 | 76.3 | 65.6 | [config](configs/body/2d_kpt_sview_rgb_img/topdown_heatmap/crowdpose/ViTPose_huge_crowdpose_256x192.py) | [Onedrive](https://1drv.ms/u/s!AimBgYV7JjTlgS-oAvEV4MTD--Xr?e=EeW2Fu) | | ViTPose-G | COCO+AIC+MPII+CrowdPose | 576x432 | 78.3 | 67.9 | | | -## Results from this repo on MPII val set (multi task training) +## Results from this repo on MPII val set (multi-task training) Using groundtruth bounding boxes. Note the configs here are only for evaluation. The metric is PCKh. @@ -83,7 +83,7 @@ Using groundtruth bounding boxes. Note the configs here are only for evaluation. | ViTPose-H | COCO+AIC+MPII+CrowdPose | 256x192 | 94.1 | [config](configs/body/2d_kpt_sview_rgb_img/topdown_heatmap/mpii/ViTPose_huge_mpii_256x192.py) | [Onedrive](https://1drv.ms/u/s!AimBgYV7JjTlgTT90XEQBKy-scIH?e=D2WhTS) | | ViTPose-G | COCO+AIC+MPII+CrowdPose | 576x432 | 94.3 | | | -## Results from this repo on AI Challenger test set (multi task training) +## Results from this repo on AI Challenger test set (multi-task training) Using groundtruth bounding boxes. Note the configs here are only for evaluation. @@ -96,6 +96,8 @@ Using groundtruth bounding boxes. Note the configs here are only for evaluation. ## Updates +> [2022-05-24] Upload the single-task training code, single-task pre-trained models, and multi-task pretrained models. + > [2022-05-06] Upload the logs for the base, large, and huge models! > [2022-04-27] Our ViTPose with ViTAE-G obtains 81.1 AP on COCO test-dev set!